From 95fe8e8406448c3cd757644854100984eeeac5f8 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 9 Nov 2024 00:11:28 +0000
Subject: [PATCH 01/82] Initial stuff for reading bloom filter from PQ files

---
 .../io/parquet/compact_protocol_reader.cpp    |  33 +++-
 .../io/parquet/compact_protocol_reader.hpp    |   4 +
 cpp/src/io/parquet/parquet.hpp                |  45 +++++
 .../io/parquet/reader_apply_bloom_filters.cu  |  36 ++++
 cpp/src/io/parquet/reader_impl_helpers.cpp    | 178 ++++++++++++++++++
 cpp/src/io/parquet/reader_impl_helpers.hpp    |  25 ++-
 cpp/src/io/parquet/reader_impl_preprocess.cu  |   3 +-
 7 files changed, 321 insertions(+), 3 deletions(-)
 create mode 100644 cpp/src/io/parquet/reader_apply_bloom_filters.cu

diff --git a/cpp/src/io/parquet/compact_protocol_reader.cpp b/cpp/src/io/parquet/compact_protocol_reader.cpp
index d276e946a51..55874822ade 100644
--- a/cpp/src/io/parquet/compact_protocol_reader.cpp
+++ b/cpp/src/io/parquet/compact_protocol_reader.cpp
@@ -655,6 +655,33 @@ void CompactProtocolReader::read(ColumnChunk* c)
   function_builder(this, op);
 }
 
+void CompactProtocolReader::read(BloomFilterAlgorithm* alg)
+{
+  auto op = std::make_tuple(parquet_field_union_enumerator(1, alg->algorithm));
+  function_builder(this, op);
+}
+
+void CompactProtocolReader::read(BloomFilterHash* hash)
+{
+  auto op = std::make_tuple(parquet_field_union_enumerator(1, hash->hash));
+  function_builder(this, op);
+}
+
+void CompactProtocolReader::read(BloomFilterCompression* comp)
+{
+  auto op = std::make_tuple(parquet_field_union_enumerator(1, comp->compression));
+  function_builder(this, op);
+}
+
+void CompactProtocolReader::read(BloomFilterHeader* bf)
+{
+  auto op = std::make_tuple(parquet_field_int32(1, bf->num_bytes),
+                            parquet_field_struct(2, bf->algorithm),
+                            parquet_field_struct(3, bf->hash),
+                            parquet_field_struct(4, bf->compression));
+  function_builder(this, op);
+}
+
 void CompactProtocolReader::read(ColumnChunkMetaData* c)
 {
   using optional_size_statistics =
@@ -662,7 +689,9 @@ void CompactProtocolReader::read(ColumnChunkMetaData* c)
   using optional_list_enc_stats =
     parquet_field_optional<std::vector<PageEncodingStats>,
                            parquet_field_struct_list<PageEncodingStats>>;
-  auto op = std::make_tuple(parquet_field_enum<Type>(1, c->type),
+  using optional_i64 = parquet_field_optional<int64_t, parquet_field_int64>;
+  using optional_i32 = parquet_field_optional<int32_t, parquet_field_int32>;
+  auto op            = std::make_tuple(parquet_field_enum<Type>(1, c->type),
                             parquet_field_enum_list(2, c->encodings),
                             parquet_field_string_list(3, c->path_in_schema),
                             parquet_field_enum<Compression>(4, c->codec),
@@ -674,6 +703,8 @@ void CompactProtocolReader::read(ColumnChunkMetaData* c)
                             parquet_field_int64(11, c->dictionary_page_offset),
                             parquet_field_struct(12, c->statistics),
                             optional_list_enc_stats(13, c->encoding_stats),
+                            optional_i64(14, c->bloom_filter_offset),
+                            optional_i32(15, c->bloom_filter_length),
                             optional_size_statistics(16, c->size_statistics));
   function_builder(this, op);
 }
diff --git a/cpp/src/io/parquet/compact_protocol_reader.hpp b/cpp/src/io/parquet/compact_protocol_reader.hpp
index b87f2e9c692..3d39daa60d1 100644
--- a/cpp/src/io/parquet/compact_protocol_reader.hpp
+++ b/cpp/src/io/parquet/compact_protocol_reader.hpp
@@ -108,6 +108,10 @@ class CompactProtocolReader {
   void read(IntType* t);
   void read(RowGroup* r);
   void read(ColumnChunk* c);
+  void read(BloomFilterAlgorithm* bf);
+  void read(BloomFilterHash* bf);
+  void read(BloomFilterCompression* bf);
+  void read(BloomFilterHeader* bf);
   void read(ColumnChunkMetaData* c);
   void read(PageHeader* p);
   void read(DataPageHeader* d);
diff --git a/cpp/src/io/parquet/parquet.hpp b/cpp/src/io/parquet/parquet.hpp
index 2851ef67a65..118ec43133b 100644
--- a/cpp/src/io/parquet/parquet.hpp
+++ b/cpp/src/io/parquet/parquet.hpp
@@ -382,12 +382,57 @@ struct ColumnChunkMetaData {
   // Set of all encodings used for pages in this column chunk. This information can be used to
   // determine if all data pages are dictionary encoded for example.
   std::optional<std::vector<PageEncodingStats>> encoding_stats;
+  // Byte offset from beginning of file to Bloom filter data.
+  std::optional<int64_t> bloom_filter_offset;
+  // Size of Bloom filter data including the serialized header, in bytes. Added in 2.10 so readers
+  // may not read this field from old files and it can be obtained after the BloomFilterHeader has
+  // been deserialized. Writers should write this field so readers can read the bloom filter in a
+  // single I/O.
+  std::optional<int32_t> bloom_filter_length;
   // Optional statistics to help estimate total memory when converted to in-memory representations.
   // The histograms contained in these statistics can also be useful in some cases for more
   // fine-grained nullability/list length filter pushdown.
   std::optional<SizeStatistics> size_statistics;
 };
 
+/**
+ * @brief The algorithm used in Bloom filter.
+ **/
+struct BloomFilterAlgorithm {
+  /** Block-based Bloom filter. **/
+  enum Algorithm { UNDEFINED, SPLIT_BLOCK };
+  Algorithm algorithm{Algorithm::SPLIT_BLOCK};
+};
+
+/**
+ * @brief The hash function used in Bloom filter. This function takes the hash of a column value
+ * using plain encoding.
+ **/
+struct BloomFilterHash {
+  /** xxHash Strategy. **/
+  enum Hash { UNDEFINED, XXHASH };
+  Hash hash{Hash::XXHASH};
+};
+
+/**
+ * @brief The compression used in the Bloom filter.
+ **/
+struct BloomFilterCompression {
+  enum Compression { UNDEFINED, UNCOMPRESSED };
+  Compression compression{Compression::UNCOMPRESSED};
+};
+
+struct BloomFilterHeader {
+  // The size of bitset in bytes
+  int32_t num_bytes;
+  // The algorithm for setting bits. *
+  BloomFilterAlgorithm algorithm;
+  // The hash function used for Bloom filter. *
+  BloomFilterHash hash;
+  // The compression used in the Bloom filter *
+  BloomFilterCompression compression;
+};
+
 /**
  * @brief Thrift-derived struct describing a chunk of data for a particular
  * column
diff --git a/cpp/src/io/parquet/reader_apply_bloom_filters.cu b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
new file mode 100644
index 00000000000..2d1c20ba48c
--- /dev/null
+++ b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
@@ -0,0 +1,36 @@
+/*
+ * Copyright (c) 2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/**
+ * @file bloom_filter_reader.cu
+ * @brief Bloom filter reader based row group filtration implementation
+ */
+
+#include "parquet.hpp"
+#include "parquet_common.hpp"
+
+#include <cudf/utilities/error.hpp>
+
+#include <cuco/bloom_filter.cuh>
+
+#include <algorithm>
+#include <cstddef>
+#include <functional>
+#include <optional>
+#include <tuple>
+
+// TODO: Implement this
+cuda::std::optional<std::vector<std::vector<cudf::size_type>>> apply_bloom_filters() { return {}; }
\ No newline at end of file
diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index a6562d33de2..b6348a3f897 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -25,11 +25,16 @@
 
 #include <cudf/detail/utilities/logger.hpp>
 
+#include <rmm/cuda_stream_view.hpp>
+#include <rmm/device_buffer.hpp>
+
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/iterator/zip_iterator.h>
 
 #include <functional>
+#include <future>
 #include <numeric>
+#include <optional>
 #include <regex>
 
 namespace cudf::io::parquet::detail {
@@ -1028,8 +1033,169 @@ std::vector<std::string> aggregate_reader_metadata::get_pandas_index_names() con
   return names;
 }
 
+/**
+ * @brief Asynchronously reads bloom filters to device.
+ *
+ * @param sources Dataset sources
+ * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
+ * @param chunks List of chunk indices to read
+ * @param bloom_filter_offsets Bloom filter offsets for all chunks
+ * @param bloom_filter_sizes Bloom filter sizes for all chunks
+ * @param chunk_source_map Association between each column chunk and its source
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ *
+ * @return A future object for reading synchronization
+ */
+std::future<void> read_bloom_filters_async(
+  host_span<std::unique_ptr<datasource> const> sources,
+  cudf::host_span<rmm::device_buffer> bloom_filter_data,
+  host_span<size_type const> chunks,
+  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
+  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
+  std::vector<size_type> const& chunk_source_map,
+  rmm::cuda_stream_view stream)
+{
+  // Transfer bloom filter data
+  std::vector<std::future<size_t>> read_tasks;
+
+  // FIXME: Do not read all chunks. Instead use a list of chunks to read.
+  for (auto chunk : chunks) {
+    // Read bloom filter if present
+    if (bloom_filter_offsets[chunk].has_value()) {
+      auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
+      // If Bloom filter size (header + bitset) is available, just read the entire thing.
+      // Else just read 256 bytes which will contain the entire header and may contain the
+      // entire bitset as well.
+      auto constexpr bloom_filter_header_size_guess = 256;
+      auto const initial_read_size =
+        bloom_filter_sizes[chunk].value_or(bloom_filter_header_size_guess);
+
+      // Read an initial buffer from source
+      auto& source = sources[chunk_source_map[chunk]];
+      auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
+
+      // Deserialize the Bloom filter header from the buffer.
+      BloomFilterHeader header;
+      CompactProtocolReader cp{buffer->data(), buffer->size()};
+      cp.read(&header);
+
+      // Bloom filter header size
+      auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
+      auto const bitset_size              = header.num_bytes;
+
+      // Check if we already read in the filter bitset in the initial read.
+      if (initial_read_size >= bloom_filter_header_size + bitset_size) {
+        bloom_filter_data[chunk] =
+          rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
+      }
+      // Read the bitset from datasource.
+      else {
+        auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
+        // Directly read to device if preferred
+        if (source->is_device_read_preferred(bitset_size)) {
+          bloom_filter_data[chunk] = rmm::device_buffer(bitset_size, stream);
+          auto future_read_size =
+            source->device_read_async(bitset_offset,
+                                      bitset_size,
+                                      static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
+                                      stream);
+
+          read_tasks.emplace_back(std::move(future_read_size));
+        } else {
+          buffer                   = source->host_read(bitset_offset, bitset_size);
+          bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
+        }
+      }
+    }
+  }
+  auto sync_fn = [](decltype(read_tasks) read_tasks) {
+    for (auto& task : read_tasks) {
+      task.wait();
+    }
+  };
+  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
+}
+
+std::optional<std::vector<std::vector<size_type>>>
+aggregate_reader_metadata::apply_bloom_filter_to_row_groups(
+  host_span<std::unique_ptr<datasource> const> sources,
+  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<data_type const> output_dtypes,
+  host_span<int const> output_column_schemas,
+  rmm::cuda_stream_view stream) const
+{
+  // Number of row groups after filter_row_groups().
+  auto const num_row_groups = std::accumulate(
+    row_group_indices.begin(), row_group_indices.end(), 0, [](auto& sum, auto const& rgis) {
+      return sum + rgis.size();
+    });
+  // Descriptors for all the chunks that make up the selected columns
+  auto const num_input_columns = output_dtypes.size();
+  auto const num_chunks        = num_row_groups * num_input_columns;
+
+  // Association between each column chunk and its source
+  std::vector<size_type> chunk_source_map(num_chunks);
+
+  // Keep track of column chunk file offsets
+  std::vector<std::optional<int64_t>> bloom_filter_offsets(num_chunks);
+  std::vector<std::optional<int32_t>> bloom_filter_sizes(num_chunks);
+
+  // List of chunks to read
+  std::vector<size_type> chunks_to_read{};
+  chunks_to_read.reserve(num_chunks);
+
+  size_type chunk_count = 0;
+
+  // FIXME: We don't need to read bloom filters for all chunks. Only the ones belonging to the
+  // columns of our interest (equality predicate).
+  // For all data sources
+  for (size_t rg_source_index = 0; rg_source_index < row_group_indices.size(); rg_source_index++) {
+    auto const& rg_index = row_group_indices[rg_source_index];
+    // For all row groups in a data source
+    for (auto const rgi : rg_index) {
+      // For all column chunks in a row group
+      for (size_t col_idx = 0; col_idx < output_dtypes.size(); col_idx++) {
+        auto const schema_idx = output_column_schemas[col_idx];
+        auto& col_meta        = get_column_metadata(rgi, rg_source_index, schema_idx);
+
+        // Bloom filter offsets and sizes
+        bloom_filter_offsets[chunk_count] = col_meta.bloom_filter_offset;
+        bloom_filter_sizes[chunk_count]   = col_meta.bloom_filter_length;
+        chunks_to_read.emplace_back(chunk_count);
+
+        // Map each column chunk to its column index and its source index
+        chunk_source_map[chunk_count] = rg_source_index;
+        chunk_count++;
+      }
+    }
+  }
+
+  // Do we have any bloom filters
+  if (std::any_of(bloom_filter_offsets.cbegin(),
+                  bloom_filter_offsets.cend(),
+                  [](auto const offset) { return offset.has_value(); })) {
+    // Initialize the vector of bloom filter data buffers
+    std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
+
+    // Wait on bloom filter read tasks
+    read_bloom_filters_async(sources,
+                             bloom_filter_data,
+                             chunks_to_read,
+                             bloom_filter_offsets,
+                             bloom_filter_sizes,
+                             chunk_source_map,
+                             stream)
+      .wait();
+
+    // Apply bloom filter to row groups
+    // return apply_bloom_filters();
+  }
+  return {};
+}
+
 std::tuple<int64_t, size_type, std::vector<row_group_info>, std::vector<size_t>>
 aggregate_reader_metadata::select_row_groups(
+  host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
   int64_t skip_rows_opt,
   std::optional<size_type> const& num_rows_opt,
@@ -1048,6 +1214,18 @@ aggregate_reader_metadata::select_row_groups(
         host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
     }
   }
+
+  // FIXME: Provide the actual condition for this if
+  if (true /* equality predicate provided */) {
+    filtered_row_group_indices = apply_bloom_filter_to_row_groups(
+      sources, row_group_indices, output_dtypes, output_column_schemas, stream);
+
+    if (filtered_row_group_indices.has_value()) {
+      row_group_indices =
+        host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
+    }
+  }
+
   std::vector<row_group_info> selection;
   auto [rows_to_skip, rows_to_read] = [&]() {
     if (not row_group_indices.empty()) { return std::pair<int64_t, size_type>{}; }
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index fd692c0cdd6..82228599cd4 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -343,6 +343,7 @@ class aggregate_reader_metadata {
    * The input `row_start` and `row_count` parameters will be recomputed and output as the valid
    * values based on the input row group list.
    *
+   * @param sources Lists of input datasources.
    * @param row_group_indices Lists of row groups to read, one per source
    * @param row_start Starting row of the selection
    * @param row_count Total number of rows selected
@@ -354,7 +355,8 @@ class aggregate_reader_metadata {
    *         starting row, and list of number of rows per source.
    */
   [[nodiscard]] std::tuple<int64_t, size_type, std::vector<row_group_info>, std::vector<size_t>>
-  select_row_groups(host_span<std::vector<size_type> const> row_group_indices,
+  select_row_groups(host_span<std::unique_ptr<datasource> const> sources,
+                    host_span<std::vector<size_type> const> row_group_indices,
                     int64_t row_start,
                     std::optional<size_type> const& row_count,
                     host_span<data_type const> output_dtypes,
@@ -362,6 +364,27 @@ class aggregate_reader_metadata {
                     std::optional<std::reference_wrapper<ast::expression const>> filter,
                     rmm::cuda_stream_view stream) const;
 
+  /**
+   * @brief Filters the row groups using bloom filters
+   *
+   * @param sources Dataset sources
+   * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
+   * @param begin_chunk Index of first column chunk to read
+   * @param end_chunk Index after the last column chunk to read
+   * @param bloom_filter_offsets Bloom filter offsets for all chunks
+   * @param bloom_filter_sizes Bloom filter sizes for all chunks
+   * @param chunk_source_map Association between each column chunk and its source
+   * @param stream CUDA stream used for device memory operations and kernel launches
+   *
+   * @return Filtered row group indices, if any is filtered.
+   */
+  std::optional<std::vector<std::vector<size_type>>> apply_bloom_filter_to_row_groups(
+    host_span<std::unique_ptr<datasource> const> sources,
+    host_span<std::vector<size_type> const> row_group_indices,
+    host_span<data_type const> output_dtypes,
+    host_span<int const> output_column_schemas,
+    rmm::cuda_stream_view stream) const;
+
   /**
    * @brief Filters and reduces down to a selection of columns
    *
diff --git a/cpp/src/io/parquet/reader_impl_preprocess.cu b/cpp/src/io/parquet/reader_impl_preprocess.cu
index f03f1214b9a..7c169f0e6ca 100644
--- a/cpp/src/io/parquet/reader_impl_preprocess.cu
+++ b/cpp/src/io/parquet/reader_impl_preprocess.cu
@@ -1281,7 +1281,8 @@ void reader::impl::preprocess_file(read_mode mode)
            _file_itm_data.global_num_rows,
            _file_itm_data.row_groups,
            _file_itm_data.num_rows_per_source) =
-    _metadata->select_row_groups(_options.row_group_indices,
+    _metadata->select_row_groups(_sources,
+                                 _options.row_group_indices,
                                  _options.skip_rows,
                                  _options.num_rows,
                                  output_dtypes,

From 4f0e7ab2b309a9cf7cb552523850fd4298df76c4 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 9 Nov 2024 00:22:21 +0000
Subject: [PATCH 02/82] Minor bug fix

---
 cpp/src/io/parquet/reader_impl_helpers.cpp | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index b6348a3f897..da000edfd04 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -1215,12 +1215,13 @@ aggregate_reader_metadata::select_row_groups(
     }
   }
 
-  // FIXME: Provide the actual condition for this if
+  // FIXME: Provide the actual condition for this
   if (true /* equality predicate provided */) {
-    filtered_row_group_indices = apply_bloom_filter_to_row_groups(
+    auto const bloom_filtered_row_groups = apply_bloom_filter_to_row_groups(
       sources, row_group_indices, output_dtypes, output_column_schemas, stream);
-
-    if (filtered_row_group_indices.has_value()) {
+    // TODO: Can use a better logic here.
+    if (bloom_filtered_row_groups.has_value()) {
+      filtered_row_group_indices.value() = std::move(bloom_filtered_row_groups.value());
       row_group_indices =
         host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
     }

From 48a50c401aafb12bf7f29645092601b174a822f8 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 9 Nov 2024 00:22:55 +0000
Subject: [PATCH 03/82] Apply style fix

---
 cpp/src/io/parquet/reader_apply_bloom_filters.cu | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/reader_apply_bloom_filters.cu b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
index 2d1c20ba48c..fc85a0a1eb2 100644
--- a/cpp/src/io/parquet/reader_apply_bloom_filters.cu
+++ b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
@@ -33,4 +33,4 @@
 #include <tuple>
 
 // TODO: Implement this
-cuda::std::optional<std::vector<std::vector<cudf::size_type>>> apply_bloom_filters() { return {}; }
\ No newline at end of file
+cuda::std::optional<std::vector<std::vector<cudf::size_type>>> apply_bloom_filters() { return {}; }

From 68be24f204857c75ea10b85aebf6209d50677929 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 16 Nov 2024 03:12:55 +0000
Subject: [PATCH 04/82] Some updates

---
 cpp/src/io/parquet/predicate_pushdown.cpp  | 14 +++++++
 cpp/src/io/parquet/reader_impl_helpers.cpp | 44 +++++++++++++---------
 cpp/src/io/parquet/reader_impl_helpers.hpp |  2 +
 3 files changed, 43 insertions(+), 17 deletions(-)

diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index cd3dcd2bce4..abc8978d8db 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -391,6 +391,7 @@ class stats_expression_converter : public ast::detail::expression_transformer {
 }  // namespace
 
 std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::filter_row_groups(
+  host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
   host_span<data_type const> output_dtypes,
   host_span<int const> output_column_schemas,
@@ -491,6 +492,19 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
     }
     filtered_row_group_indices.push_back(std::move(filtered_row_groups));
   }
+
+  // If equality predicate
+  if (true /* is_equality_predicate */) {
+    filtered_row_group_indices =
+      apply_bloom_filter_to_row_groups(
+        sources,
+        filtered_row_group_indices.empty() ? input_row_group_indices : filtered_row_group_indices,
+        output_dtypes,
+        output_column_schemas,
+        stream)
+        .value();
+  }
+
   return {std::move(filtered_row_group_indices)};
 }
 
diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index da000edfd04..7ca1ffc4253 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -1079,6 +1079,20 @@ std::future<void> read_bloom_filters_async(
       CompactProtocolReader cp{buffer->data(), buffer->size()};
       cp.read(&header);
 
+      // Test if header is valid.
+      auto const is_header_valid =
+        (header.num_bytes % 32) == 0 and
+        header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
+        header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
+        header.hash.hash == BloomFilterHash::Hash::XXHASH;
+
+      if (not is_header_valid) {
+        // Simply use an empty device buffer and move on.
+        bloom_filter_data[chunk] = rmm::device_buffer{};
+        CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
+        continue;
+      }
+
       // Bloom filter header size
       auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
       auto const bitset_size              = header.num_bytes;
@@ -1106,6 +1120,9 @@ std::future<void> read_bloom_filters_async(
           bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
         }
       }
+    } else {
+      // Simply use an empty device buffer.
+      bloom_filter_data[chunk] = rmm::device_buffer{};
     }
   }
   auto sync_fn = [](decltype(read_tasks) read_tasks) {
@@ -1124,11 +1141,16 @@ aggregate_reader_metadata::apply_bloom_filter_to_row_groups(
   host_span<int const> output_column_schemas,
   rmm::cuda_stream_view stream) const
 {
-  // Number of row groups after filter_row_groups().
-  auto const num_row_groups = std::accumulate(
-    row_group_indices.begin(), row_group_indices.end(), 0, [](auto& sum, auto const& rgis) {
-      return sum + rgis.size();
-    });
+  // Create row group indices.
+  // std::vector<std::vector<size_type>> filtered_row_group_indices;
+  // Number of total row groups to process.
+  auto const num_row_groups = std::accumulate(row_group_indices.begin(),
+                                              row_group_indices.end(),
+                                              0,
+                                              [](size_type sum, auto const& per_file_row_groups) {
+                                                return sum + per_file_row_groups.size();
+                                              });
+
   // Descriptors for all the chunks that make up the selected columns
   auto const num_input_columns = output_dtypes.size();
   auto const num_chunks        = num_row_groups * num_input_columns;
@@ -1215,18 +1237,6 @@ aggregate_reader_metadata::select_row_groups(
     }
   }
 
-  // FIXME: Provide the actual condition for this
-  if (true /* equality predicate provided */) {
-    auto const bloom_filtered_row_groups = apply_bloom_filter_to_row_groups(
-      sources, row_group_indices, output_dtypes, output_column_schemas, stream);
-    // TODO: Can use a better logic here.
-    if (bloom_filtered_row_groups.has_value()) {
-      filtered_row_group_indices.value() = std::move(bloom_filtered_row_groups.value());
-      row_group_indices =
-        host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
-    }
-  }
-
   std::vector<row_group_info> selection;
   auto [rows_to_skip, rows_to_read] = [&]() {
     if (not row_group_indices.empty()) { return std::pair<int64_t, size_type>{}; }
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 82228599cd4..7faae405b4a 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -323,6 +323,7 @@ class aggregate_reader_metadata {
   /**
    * @brief Filters the row groups based on predicate filter
    *
+   * @param sources Lists of input datasources.
    * @param row_group_indices Lists of row groups to read, one per source
    * @param output_dtypes Datatypes of of output columns
    * @param output_column_schemas schema indices of output columns
@@ -331,6 +332,7 @@ class aggregate_reader_metadata {
    * @return Filtered row group indices, if any is filtered.
    */
   [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> filter_row_groups(
+    host_span<std::unique_ptr<datasource> const> sources,
     host_span<std::vector<size_type> const> row_group_indices,
     host_span<data_type const> output_dtypes,
     host_span<int const> output_column_schemas,

From f84825126e3eba2a3d3bd7ed7e11e341541687ed Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 16 Nov 2024 05:04:13 +0000
Subject: [PATCH 05/82] Move contents to a separate file

---
 cpp/src/io/parquet/bloom_filter_reader.cpp | 209 +++++++++++++++++++++
 cpp/src/io/parquet/predicate_pushdown.cpp  |  12 --
 cpp/src/io/parquet/reader_impl_helpers.cpp | 184 +-----------------
 cpp/src/io/parquet/reader_impl_helpers.hpp |  19 +-
 4 files changed, 218 insertions(+), 206 deletions(-)
 create mode 100644 cpp/src/io/parquet/bloom_filter_reader.cpp

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cpp b/cpp/src/io/parquet/bloom_filter_reader.cpp
new file mode 100644
index 00000000000..346ccd22c58
--- /dev/null
+++ b/cpp/src/io/parquet/bloom_filter_reader.cpp
@@ -0,0 +1,209 @@
+/*
+ * Copyright (c) 2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "compact_protocol_reader.hpp"
+#include "io/parquet/parquet.hpp"
+#include "reader_impl_helpers.hpp"
+
+#include <cudf/detail/utilities/logger.hpp>
+
+#include <rmm/cuda_stream_view.hpp>
+#include <rmm/device_buffer.hpp>
+
+#include <thrust/iterator/counting_iterator.h>
+
+#include <future>
+#include <numeric>
+#include <optional>
+
+namespace cudf::io::parquet::detail {
+
+namespace {
+/**
+ * @brief Asynchronously reads bloom filters to device.
+ *
+ * @param sources Dataset sources
+ * @param num_chunks Number of total column chunks to read
+ * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
+ * @param bloom_filter_offsets Bloom filter offsets for all chunks
+ * @param bloom_filter_sizes Bloom filter sizes for all chunks
+ * @param chunk_source_map Association between each column chunk and its source
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ *
+ * @return A future object for reading synchronization
+ */
+std::future<void> read_bloom_filters_async(
+  host_span<std::unique_ptr<datasource> const> sources,
+  size_t num_chunks,
+  cudf::host_span<rmm::device_buffer> bloom_filter_data,
+  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
+  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
+  std::vector<size_type> const& chunk_source_map,
+  rmm::cuda_stream_view stream)
+{
+  // Read tasks for bloom filter data
+  std::vector<std::future<size_t>> read_tasks;
+
+  // Read bloom filters for all column chunks
+  std::for_each(
+    thrust::make_counting_iterator<size_t>(0),
+    thrust::make_counting_iterator<size_t>(num_chunks),
+    [&](auto const chunk) {
+      // Read bloom filter if present
+      if (bloom_filter_offsets[chunk].has_value()) {
+        auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
+        // If Bloom filter size (header + bitset) is available, just read the entire thing.
+        // Else just read 256 bytes which will contain the entire header and may contain the
+        // entire bitset as well.
+        auto constexpr bloom_filter_header_size_guess = 256;
+        auto const initial_read_size =
+          bloom_filter_sizes[chunk].value_or(bloom_filter_header_size_guess);
+
+        // Read an initial buffer from source
+        auto& source = sources[chunk_source_map[chunk]];
+        auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
+
+        // Deserialize the Bloom filter header from the buffer.
+        BloomFilterHeader header;
+        CompactProtocolReader cp{buffer->data(), buffer->size()};
+        cp.read(&header);
+
+        // Test if header is valid.
+        auto const is_header_valid =
+          (header.num_bytes % 32) == 0 and
+          header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
+          header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
+          header.hash.hash == BloomFilterHash::Hash::XXHASH;
+
+        // Do not read if the bloom filter is invalid
+        if (not is_header_valid) {
+          CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
+          return;
+        }
+
+        // Bloom filter header size
+        auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
+        auto const bitset_size              = header.num_bytes;
+
+        // Check if we already read in the filter bitset in the initial read.
+        if (initial_read_size >= bloom_filter_header_size + bitset_size) {
+          bloom_filter_data[chunk] =
+            rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
+        }
+        // Read the bitset from datasource.
+        else {
+          auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
+          // Directly read to device if preferred
+          if (source->is_device_read_preferred(bitset_size)) {
+            bloom_filter_data[chunk] = rmm::device_buffer(bitset_size, stream);
+            auto future_read_size =
+              source->device_read_async(bitset_offset,
+                                        bitset_size,
+                                        static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
+                                        stream);
+
+            read_tasks.emplace_back(std::move(future_read_size));
+          } else {
+            buffer                   = source->host_read(bitset_offset, bitset_size);
+            bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
+          }
+        }
+      }
+    });
+  auto sync_fn = [](decltype(read_tasks) read_tasks) {
+    for (auto& task : read_tasks) {
+      task.wait();
+    }
+  };
+  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
+}
+
+}  // namespace
+
+std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
+  host_span<std::unique_ptr<datasource> const> sources,
+  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<int const> column_schemas,
+  rmm::cuda_stream_view stream) const
+{
+  // Number of total row groups to process.
+  auto const num_row_groups = std::accumulate(
+    row_group_indices.begin(),
+    row_group_indices.end(),
+    size_t{0},
+    [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
+
+  // Descriptors for all the chunks that make up the selected columns
+  auto const num_input_columns = column_schemas.size();
+  auto const num_chunks        = num_row_groups * num_input_columns;
+
+  // Association between each column chunk and its source
+  std::vector<size_type> chunk_source_map(num_chunks);
+
+  // Keep track of column chunk file offsets
+  std::vector<std::optional<int64_t>> bloom_filter_offsets(num_chunks);
+  std::vector<std::optional<int32_t>> bloom_filter_sizes(num_chunks);
+
+  // Gather all bloom filter offsets and sizes.
+  size_type chunk_count = 0;
+
+  // For all data sources
+  std::for_each(thrust::make_counting_iterator<size_t>(0),
+                thrust::make_counting_iterator(row_group_indices.size()),
+                [&](auto const src_index) {
+                  // Get all row group indices in the data source
+                  auto const& rg_indices = row_group_indices[src_index];
+                  // For all row groups
+                  std::for_each(rg_indices.cbegin(), rg_indices.cend(), [&](auto const rg_index) {
+                    // For all column chunks
+                    std::for_each(
+                      column_schemas.begin(), column_schemas.end(), [&](auto const schema_idx) {
+                        auto& col_meta = get_column_metadata(rg_index, src_index, schema_idx);
+
+                        // Get bloom filter offsets and sizes
+                        bloom_filter_offsets[chunk_count] = col_meta.bloom_filter_offset;
+                        bloom_filter_sizes[chunk_count]   = col_meta.bloom_filter_length;
+
+                        // Map each column chunk to its source index
+                        chunk_source_map[chunk_count] = src_index;
+                        chunk_count++;
+                      });
+                  });
+                });
+
+  // Do we have any bloom filters
+  if (std::any_of(bloom_filter_offsets.cbegin(),
+                  bloom_filter_offsets.cend(),
+                  [](auto const offset) { return offset.has_value(); })) {
+    // Create a vector to store bloom filter data
+    std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
+
+    // Wait on bloom filter read tasks
+    read_bloom_filters_async(sources,
+                             num_chunks,
+                             bloom_filter_data,
+                             bloom_filter_offsets,
+                             bloom_filter_sizes,
+                             chunk_source_map,
+                             stream)
+      .wait();
+    // Return the vector
+    return bloom_filter_data;
+  }
+  return {};
+}
+
+}  // namespace cudf::io::parquet::detail
\ No newline at end of file
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index abc8978d8db..a977cfdeca7 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -493,18 +493,6 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
     filtered_row_group_indices.push_back(std::move(filtered_row_groups));
   }
 
-  // If equality predicate
-  if (true /* is_equality_predicate */) {
-    filtered_row_group_indices =
-      apply_bloom_filter_to_row_groups(
-        sources,
-        filtered_row_group_indices.empty() ? input_row_group_indices : filtered_row_group_indices,
-        output_dtypes,
-        output_column_schemas,
-        stream)
-        .value();
-  }
-
   return {std::move(filtered_row_group_indices)};
 }
 
diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index 7ca1ffc4253..9c05009b528 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -1033,188 +1033,6 @@ std::vector<std::string> aggregate_reader_metadata::get_pandas_index_names() con
   return names;
 }
 
-/**
- * @brief Asynchronously reads bloom filters to device.
- *
- * @param sources Dataset sources
- * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
- * @param chunks List of chunk indices to read
- * @param bloom_filter_offsets Bloom filter offsets for all chunks
- * @param bloom_filter_sizes Bloom filter sizes for all chunks
- * @param chunk_source_map Association between each column chunk and its source
- * @param stream CUDA stream used for device memory operations and kernel launches
- *
- * @return A future object for reading synchronization
- */
-std::future<void> read_bloom_filters_async(
-  host_span<std::unique_ptr<datasource> const> sources,
-  cudf::host_span<rmm::device_buffer> bloom_filter_data,
-  host_span<size_type const> chunks,
-  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
-  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
-  std::vector<size_type> const& chunk_source_map,
-  rmm::cuda_stream_view stream)
-{
-  // Transfer bloom filter data
-  std::vector<std::future<size_t>> read_tasks;
-
-  // FIXME: Do not read all chunks. Instead use a list of chunks to read.
-  for (auto chunk : chunks) {
-    // Read bloom filter if present
-    if (bloom_filter_offsets[chunk].has_value()) {
-      auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
-      // If Bloom filter size (header + bitset) is available, just read the entire thing.
-      // Else just read 256 bytes which will contain the entire header and may contain the
-      // entire bitset as well.
-      auto constexpr bloom_filter_header_size_guess = 256;
-      auto const initial_read_size =
-        bloom_filter_sizes[chunk].value_or(bloom_filter_header_size_guess);
-
-      // Read an initial buffer from source
-      auto& source = sources[chunk_source_map[chunk]];
-      auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
-
-      // Deserialize the Bloom filter header from the buffer.
-      BloomFilterHeader header;
-      CompactProtocolReader cp{buffer->data(), buffer->size()};
-      cp.read(&header);
-
-      // Test if header is valid.
-      auto const is_header_valid =
-        (header.num_bytes % 32) == 0 and
-        header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
-        header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
-        header.hash.hash == BloomFilterHash::Hash::XXHASH;
-
-      if (not is_header_valid) {
-        // Simply use an empty device buffer and move on.
-        bloom_filter_data[chunk] = rmm::device_buffer{};
-        CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
-        continue;
-      }
-
-      // Bloom filter header size
-      auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
-      auto const bitset_size              = header.num_bytes;
-
-      // Check if we already read in the filter bitset in the initial read.
-      if (initial_read_size >= bloom_filter_header_size + bitset_size) {
-        bloom_filter_data[chunk] =
-          rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
-      }
-      // Read the bitset from datasource.
-      else {
-        auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
-        // Directly read to device if preferred
-        if (source->is_device_read_preferred(bitset_size)) {
-          bloom_filter_data[chunk] = rmm::device_buffer(bitset_size, stream);
-          auto future_read_size =
-            source->device_read_async(bitset_offset,
-                                      bitset_size,
-                                      static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
-                                      stream);
-
-          read_tasks.emplace_back(std::move(future_read_size));
-        } else {
-          buffer                   = source->host_read(bitset_offset, bitset_size);
-          bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
-        }
-      }
-    } else {
-      // Simply use an empty device buffer.
-      bloom_filter_data[chunk] = rmm::device_buffer{};
-    }
-  }
-  auto sync_fn = [](decltype(read_tasks) read_tasks) {
-    for (auto& task : read_tasks) {
-      task.wait();
-    }
-  };
-  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
-}
-
-std::optional<std::vector<std::vector<size_type>>>
-aggregate_reader_metadata::apply_bloom_filter_to_row_groups(
-  host_span<std::unique_ptr<datasource> const> sources,
-  host_span<std::vector<size_type> const> row_group_indices,
-  host_span<data_type const> output_dtypes,
-  host_span<int const> output_column_schemas,
-  rmm::cuda_stream_view stream) const
-{
-  // Create row group indices.
-  // std::vector<std::vector<size_type>> filtered_row_group_indices;
-  // Number of total row groups to process.
-  auto const num_row_groups = std::accumulate(row_group_indices.begin(),
-                                              row_group_indices.end(),
-                                              0,
-                                              [](size_type sum, auto const& per_file_row_groups) {
-                                                return sum + per_file_row_groups.size();
-                                              });
-
-  // Descriptors for all the chunks that make up the selected columns
-  auto const num_input_columns = output_dtypes.size();
-  auto const num_chunks        = num_row_groups * num_input_columns;
-
-  // Association between each column chunk and its source
-  std::vector<size_type> chunk_source_map(num_chunks);
-
-  // Keep track of column chunk file offsets
-  std::vector<std::optional<int64_t>> bloom_filter_offsets(num_chunks);
-  std::vector<std::optional<int32_t>> bloom_filter_sizes(num_chunks);
-
-  // List of chunks to read
-  std::vector<size_type> chunks_to_read{};
-  chunks_to_read.reserve(num_chunks);
-
-  size_type chunk_count = 0;
-
-  // FIXME: We don't need to read bloom filters for all chunks. Only the ones belonging to the
-  // columns of our interest (equality predicate).
-  // For all data sources
-  for (size_t rg_source_index = 0; rg_source_index < row_group_indices.size(); rg_source_index++) {
-    auto const& rg_index = row_group_indices[rg_source_index];
-    // For all row groups in a data source
-    for (auto const rgi : rg_index) {
-      // For all column chunks in a row group
-      for (size_t col_idx = 0; col_idx < output_dtypes.size(); col_idx++) {
-        auto const schema_idx = output_column_schemas[col_idx];
-        auto& col_meta        = get_column_metadata(rgi, rg_source_index, schema_idx);
-
-        // Bloom filter offsets and sizes
-        bloom_filter_offsets[chunk_count] = col_meta.bloom_filter_offset;
-        bloom_filter_sizes[chunk_count]   = col_meta.bloom_filter_length;
-        chunks_to_read.emplace_back(chunk_count);
-
-        // Map each column chunk to its column index and its source index
-        chunk_source_map[chunk_count] = rg_source_index;
-        chunk_count++;
-      }
-    }
-  }
-
-  // Do we have any bloom filters
-  if (std::any_of(bloom_filter_offsets.cbegin(),
-                  bloom_filter_offsets.cend(),
-                  [](auto const offset) { return offset.has_value(); })) {
-    // Initialize the vector of bloom filter data buffers
-    std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
-
-    // Wait on bloom filter read tasks
-    read_bloom_filters_async(sources,
-                             bloom_filter_data,
-                             chunks_to_read,
-                             bloom_filter_offsets,
-                             bloom_filter_sizes,
-                             chunk_source_map,
-                             stream)
-      .wait();
-
-    // Apply bloom filter to row groups
-    // return apply_bloom_filters();
-  }
-  return {};
-}
-
 std::tuple<int64_t, size_type, std::vector<row_group_info>, std::vector<size_t>>
 aggregate_reader_metadata::select_row_groups(
   host_span<std::unique_ptr<datasource> const> sources,
@@ -1230,7 +1048,7 @@ aggregate_reader_metadata::select_row_groups(
   // if filter is not empty, then gather row groups to read after predicate pushdown
   if (filter.has_value()) {
     filtered_row_group_indices = filter_row_groups(
-      row_group_indices, output_dtypes, output_column_schemas, filter.value(), stream);
+      sources, row_group_indices, output_dtypes, output_column_schemas, filter.value(), stream);
     if (filtered_row_group_indices.has_value()) {
       row_group_indices =
         host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 7faae405b4a..b03aa9ec296 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -367,24 +367,21 @@ class aggregate_reader_metadata {
                     rmm::cuda_stream_view stream) const;
 
   /**
-   * @brief Filters the row groups using bloom filters
+   * @brief Reads bloom filter bitsets for the specified columns from the given lists of row
+   * groups.
    *
    * @param sources Dataset sources
-   * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
-   * @param begin_chunk Index of first column chunk to read
-   * @param end_chunk Index after the last column chunk to read
-   * @param bloom_filter_offsets Bloom filter offsets for all chunks
-   * @param bloom_filter_sizes Bloom filter sizes for all chunks
-   * @param chunk_source_map Association between each column chunk and its source
+   * @param row_group_indices Lists of row groups to read bloom filters from, one per source
+   * @param column_schemas Schema indices of columns whose bloom filters will be read
    * @param stream CUDA stream used for device memory operations and kernel launches
    *
-   * @return Filtered row group indices, if any is filtered.
+   * @return A list of bloom filter bitset device buffers flattened over column schemas over lists
+   * of row group indices
    */
-  std::optional<std::vector<std::vector<size_type>>> apply_bloom_filter_to_row_groups(
+  std::vector<rmm::device_buffer> read_bloom_filters(
     host_span<std::unique_ptr<datasource> const> sources,
     host_span<std::vector<size_type> const> row_group_indices,
-    host_span<data_type const> output_dtypes,
-    host_span<int const> output_column_schemas,
+    host_span<int const> column_schemas,
     rmm::cuda_stream_view stream) const;
 
   /**

From 0b65233026b5868aa81ac86d51327d1e1521d625 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 16 Nov 2024 05:06:19 +0000
Subject: [PATCH 06/82] Revert erroneous changes

---
 .../io/parquet/reader_apply_bloom_filters.cu  | 36 -------------------
 cpp/src/io/parquet/reader_impl_helpers.cpp    |  5 ---
 2 files changed, 41 deletions(-)
 delete mode 100644 cpp/src/io/parquet/reader_apply_bloom_filters.cu

diff --git a/cpp/src/io/parquet/reader_apply_bloom_filters.cu b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
deleted file mode 100644
index fc85a0a1eb2..00000000000
--- a/cpp/src/io/parquet/reader_apply_bloom_filters.cu
+++ /dev/null
@@ -1,36 +0,0 @@
-/*
- * Copyright (c) 2024, NVIDIA CORPORATION.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-/**
- * @file bloom_filter_reader.cu
- * @brief Bloom filter reader based row group filtration implementation
- */
-
-#include "parquet.hpp"
-#include "parquet_common.hpp"
-
-#include <cudf/utilities/error.hpp>
-
-#include <cuco/bloom_filter.cuh>
-
-#include <algorithm>
-#include <cstddef>
-#include <functional>
-#include <optional>
-#include <tuple>
-
-// TODO: Implement this
-cuda::std::optional<std::vector<std::vector<cudf::size_type>>> apply_bloom_filters() { return {}; }
diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index 9c05009b528..ae720a9622d 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -25,16 +25,11 @@
 
 #include <cudf/detail/utilities/logger.hpp>
 
-#include <rmm/cuda_stream_view.hpp>
-#include <rmm/device_buffer.hpp>
-
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/iterator/zip_iterator.h>
 
 #include <functional>
-#include <future>
 #include <numeric>
-#include <optional>
 #include <regex>
 
 namespace cudf::io::parquet::detail {

From cf7d762e26847842993dd4383f49c2fd0ca591a5 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 16 Nov 2024 05:13:54 +0000
Subject: [PATCH 07/82] Style and doc fix

---
 cpp/src/io/parquet/bloom_filter_reader.cpp |  2 +-
 cpp/src/io/parquet/parquet.hpp             | 29 +++++++++++++---------
 2 files changed, 18 insertions(+), 13 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cpp b/cpp/src/io/parquet/bloom_filter_reader.cpp
index 346ccd22c58..fabc70cc5f2 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cpp
+++ b/cpp/src/io/parquet/bloom_filter_reader.cpp
@@ -206,4 +206,4 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   return {};
 }
 
-}  // namespace cudf::io::parquet::detail
\ No newline at end of file
+}  // namespace cudf::io::parquet::detail
diff --git a/cpp/src/io/parquet/parquet.hpp b/cpp/src/io/parquet/parquet.hpp
index 118ec43133b..ff8e7a63486 100644
--- a/cpp/src/io/parquet/parquet.hpp
+++ b/cpp/src/io/parquet/parquet.hpp
@@ -396,40 +396,45 @@ struct ColumnChunkMetaData {
 };
 
 /**
- * @brief The algorithm used in Bloom filter.
- **/
+ * @brief The algorithm used in bloom filter
+ */
 struct BloomFilterAlgorithm {
-  /** Block-based Bloom filter. **/
+  // Block-based Bloom filter.
   enum Algorithm { UNDEFINED, SPLIT_BLOCK };
   Algorithm algorithm{Algorithm::SPLIT_BLOCK};
 };
 
 /**
- * @brief The hash function used in Bloom filter. This function takes the hash of a column value
- * using plain encoding.
- **/
+ * @brief The hash function used in Bloom filter
+ */
 struct BloomFilterHash {
-  /** xxHash Strategy. **/
+  // xxHash_64
   enum Hash { UNDEFINED, XXHASH };
   Hash hash{Hash::XXHASH};
 };
 
 /**
- * @brief The compression used in the Bloom filter.
- **/
+ * @brief The compression used in the bloom filter
+ */
 struct BloomFilterCompression {
   enum Compression { UNDEFINED, UNCOMPRESSED };
   Compression compression{Compression::UNCOMPRESSED};
 };
 
+/**
+ * @brief Bloom filter header struct
+ *
+ * The bloom filter data of a column chunk stores this header at the beginning
+ * following by the filter bitset.
+ */
 struct BloomFilterHeader {
   // The size of bitset in bytes
   int32_t num_bytes;
-  // The algorithm for setting bits. *
+  // The algorithm for setting bits
   BloomFilterAlgorithm algorithm;
-  // The hash function used for Bloom filter. *
+  // The hash function used for bloom filter
   BloomFilterHash hash;
-  // The compression used in the Bloom filter *
+  // The compression used in the bloom filter
   BloomFilterCompression compression;
 };
 

From 81efad2637e24f31b17b8a8d2ee25779446ddaf1 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 19 Nov 2024 03:58:42 +0000
Subject: [PATCH 08/82] Get equality predicate col indices

---
 ...lter_reader.cpp => bloom_filter_reader.cu} | 189 ++++++++++++++++++
 cpp/src/io/parquet/predicate_pushdown.cpp     |   8 +-
 cpp/src/io/parquet/reader_impl_helpers.hpp    |  20 ++
 3 files changed, 216 insertions(+), 1 deletion(-)
 rename cpp/src/io/parquet/{bloom_filter_reader.cpp => bloom_filter_reader.cu} (51%)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cpp b/cpp/src/io/parquet/bloom_filter_reader.cu
similarity index 51%
rename from cpp/src/io/parquet/bloom_filter_reader.cpp
rename to cpp/src/io/parquet/bloom_filter_reader.cu
index fabc70cc5f2..89f448de05f 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cpp
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -18,14 +18,30 @@
 #include "io/parquet/parquet.hpp"
 #include "reader_impl_helpers.hpp"
 
+#include <cudf/ast/detail/expression_transformer.hpp>
+#include <cudf/ast/detail/operators.hpp>
+#include <cudf/ast/expressions.hpp>
+#include <cudf/column/column_factories.hpp>
+#include <cudf/detail/cuco_helpers.hpp>
+#include <cudf/detail/iterator.cuh>
+#include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
+#include <cudf/utilities/error.hpp>
 
 #include <rmm/cuda_stream_view.hpp>
 #include <rmm/device_buffer.hpp>
+#include <rmm/device_vector.hpp>
+#include <rmm/exec_policy.hpp>
 
+#include <cuco/bloom_filter_policy.cuh>
+#include <cuco/bloom_filter_ref.cuh>
+#include <cuco/hash_functions.cuh>
+#include <thrust/for_each.h>
 #include <thrust/iterator/counting_iterator.h>
+#include <thrust/sequence.h>
 
 #include <future>
+#include <iterator>
 #include <numeric>
 #include <optional>
 
@@ -102,6 +118,37 @@ std::future<void> read_bloom_filters_async(
         if (initial_read_size >= bloom_filter_header_size + bitset_size) {
           bloom_filter_data[chunk] =
             rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
+
+          /* MH: Remove this
+          using word_type = uint32_t;
+
+          thrust::for_each(rmm::exec_policy(stream),
+                           thrust::make_counting_iterator(0),
+                           thrust::make_counting_iterator(1),
+                           [words = reinterpret_cast<word_type*>(bloom_filter_data[chunk].data()),
+                            num_blocks = bloom_filter_data[chunk].size() / sizeof(uint32_t),
+                            chunk      = chunk,
+                            stream     = stream] __device__(auto idx) {
+                             using key_type = cuda::std::string;
+                             using policy_type =
+                               cuco::bloom_filter_policy<cuco::xxhash_64<key_type>, std::uint32_t,
+          8>;
+                             // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
+                             cuco::bloom_filter_ref<key_type,
+                                                    cuco::extent<std::size_t>,
+                                                    cuco::thread_scope_device,
+                                                    policy_type>
+                               filter{words, size_t{num_blocks}, {}, {8}};
+                             // cuda::std::string key{"third-136666"};
+                             // filter.add("third-136666");
+
+                             cuco::xxhash_64<key_type> hasher{};
+                             cuda::std::array<char, 13> val{"third-136666"};
+                             auto hash =
+          hasher.compute_hash(reinterpret_cast<std::byte*>(val.data()), val.size()); if
+          (filter.contains(hash)) { printf("Filter chunk: %lu contains key: third-136666\n", chunk);
+                             }
+                           });*/
         }
         // Read the bitset from datasource.
         else {
@@ -123,16 +170,158 @@ std::future<void> read_bloom_filters_async(
         }
       }
     });
+
   auto sync_fn = [](decltype(read_tasks) read_tasks) {
     for (auto& task : read_tasks) {
       task.wait();
     }
   };
+
   return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
 }
 
+/**
+ * @brief Collects column indices with an equality predicate in the AST expression.
+ * This is used in row group filtering based on bloom filters.
+ */
+class equality_predicate_converter : public ast::detail::expression_transformer {
+ public:
+  equality_predicate_converter(ast::expression const& expr, size_type const& num_columns)
+    : _num_columns{num_columns}
+  {
+    expr.accept(*this);
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::literal const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override
+  {
+    _equality_expr = std::reference_wrapper<ast::expression const>(expr);
+    return expr;
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override
+  {
+    CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
+                 "Equality AST supports only left table");
+    CUDF_EXPECTS(expr.get_column_index() < _num_columns,
+                 "Column index cannot be more than number of columns in the table");
+    _equality_expr = std::reference_wrapper<ast::expression const>(expr);
+    return expr;
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_name_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(
+    ast::column_name_reference const& expr) override
+  {
+    CUDF_FAIL("Column name reference is not supported in equality AST");
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override
+  {
+    using cudf::ast::ast_operator;
+    auto const operands = expr.get_operands();
+    auto const op       = expr.get_operator();
+
+    if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
+      // First operand should be column reference, second should be literal.
+      CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
+                   "Only binary operations are supported on column reference");
+      CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
+                   "Second operand of binary operation with column reference must be a literal");
+      v->accept(*this);
+      if (op == ast_operator::EQUAL) { equality_col_idx.emplace_back(v->get_column_index()); }
+    } else {
+      auto new_operands = visit_operands(operands);
+      if (cudf::ast::detail::ast_operator_arity(op) == 2) {
+        _operators.emplace_back(op, new_operands.front(), new_operands.back());
+      } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
+        _operators.emplace_back(op, new_operands.front());
+      }
+    }
+    _equality_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    return std::reference_wrapper<ast::expression const>(_operators.back());
+  }
+
+  /**
+   * @brief Returns a list of column indices with an equality predicate in the AST expression.
+   *
+   * @return List of column indices
+   */
+  [[nodiscard]] std::vector<cudf::size_type> get_equality_col_idx() const
+  {
+    return equality_col_idx;
+  }
+
+ private:
+  std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
+    cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
+  {
+    std::vector<std::reference_wrapper<ast::expression const>> transformed_operands;
+    for (auto const& operand : operands) {
+      auto const new_operand = operand.get().accept(*this);
+      transformed_operands.push_back(new_operand);
+    }
+    return transformed_operands;
+  }
+  std::optional<std::reference_wrapper<ast::expression const>> _equality_expr;
+  std::vector<cudf::size_type> equality_col_idx;
+  size_type _num_columns;
+  std::list<ast::column_reference> _col_ref;
+  std::list<ast::operation> _operators;
+};
+
 }  // namespace
 
+std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::apply_bloom_filters(
+  host_span<std::unique_ptr<datasource> const> sources,
+  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<data_type const> output_dtypes,
+  host_span<int const> output_column_schemas,
+  std::reference_wrapper<ast::expression const> filter,
+  rmm::cuda_stream_view stream) const
+{
+  auto const num_cols = output_dtypes.size();
+  CUDF_EXPECTS(output_dtypes.size() == output_column_schemas.size(),
+               "Mismatched size between lists of output column dtypes and output column schema");
+  auto mr = cudf::get_current_device_resource_ref();
+  std::vector<std::unique_ptr<column>> cols;
+  // MH: How do I test for nested or non-comparable columns here?
+  cols.emplace_back(cudf::make_numeric_column(
+    data_type{cudf::type_id::INT32}, num_cols, rmm::device_buffer{}, 0, stream, mr));
+
+  auto mutable_col_idx = cols.back()->mutable_view();
+
+  thrust::sequence(rmm::exec_policy(stream),
+                   mutable_col_idx.begin<size_type>(),
+                   mutable_col_idx.end<size_type>(),
+                   0);
+
+  auto equality_table = cudf::table(std::move(cols));
+
+  // Converts AST to EqualityAST with reference to min, max columns in above `stats_table`.
+  equality_predicate_converter equality_expr{filter.get(), static_cast<size_type>(num_cols)};
+  auto equality_col_schemas = equality_expr.get_equality_col_idx();
+
+  // Convert column indices to column schema indices
+  std::for_each(equality_col_schemas.begin(), equality_col_schemas.end(), [&](auto& col_idx) {
+    col_idx = output_column_schemas[col_idx];
+  });
+
+  std::ignore = read_bloom_filters(sources, row_group_indices, equality_col_schemas, stream);
+
+  return std::nullopt;
+}
+
 std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index a977cfdeca7..eb30cc6955a 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -479,7 +479,9 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
                   is_row_group_required.cend(),
                   [](auto i) { return bool(i); }) or
       predicate.null_count() == predicate.size()) {
-    return std::nullopt;
+    // Call with input_row_group_indices
+    return apply_bloom_filters(
+      sources, input_row_group_indices, output_dtypes, output_column_schemas, filter, stream);
   }
   size_type is_required_idx = 0;
   for (auto const& input_row_group_index : input_row_group_indices) {
@@ -493,6 +495,10 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
     filtered_row_group_indices.push_back(std::move(filtered_row_groups));
   }
 
+  // Call with filtered_row_group_indices
+  return apply_bloom_filters(
+    sources, filtered_row_group_indices, output_dtypes, output_column_schemas, filter, stream);
+
   return {std::move(filtered_row_group_indices)};
 }
 
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index b03aa9ec296..75edfdb7f7b 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -339,6 +339,26 @@ class aggregate_reader_metadata {
     std::reference_wrapper<ast::expression const> filter,
     rmm::cuda_stream_view stream) const;
 
+  /**
+   * @brief Filters the row groups using bloom filters
+   *
+   * @param sources Dataset sources
+   * @param row_group_indices Lists of row groups to read, one per source
+   * @param output_dtypes Datatypes of of output columns
+   * @param output_column_schemas schema indices of output columns
+   * @param filter AST expression to filter row groups based on Column chunk statistics
+   * @param stream CUDA stream used for device memory operations and kernel launches
+   *
+   * @return Filtered row group indices, if any is filtered.
+   */
+  [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> apply_bloom_filters(
+    host_span<std::unique_ptr<datasource> const> sources,
+    host_span<std::vector<size_type> const> row_group_indices,
+    host_span<data_type const> output_dtypes,
+    host_span<int const> output_column_schemas,
+    std::reference_wrapper<ast::expression const> filter,
+    rmm::cuda_stream_view stream) const;
+
   /**
    * @brief Filters and reduces down to a selection of row groups
    *

From 088377b713b35b3d516c0c2c05af9e1e9815a41f Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 20 Nov 2024 02:45:46 +0000
Subject: [PATCH 09/82] Enable `arrow_filter_policy` and `span` types in bloom
 filter.

---
 cpp/src/io/parquet/arrow_filter_policy.cuh | 187 +++++++++++++++++++++
 cpp/src/io/parquet/bloom_filter_reader.cu  |  89 ++++++----
 2 files changed, 246 insertions(+), 30 deletions(-)
 create mode 100644 cpp/src/io/parquet/arrow_filter_policy.cuh

diff --git a/cpp/src/io/parquet/arrow_filter_policy.cuh b/cpp/src/io/parquet/arrow_filter_policy.cuh
new file mode 100644
index 00000000000..95edf68cab4
--- /dev/null
+++ b/cpp/src/io/parquet/arrow_filter_policy.cuh
@@ -0,0 +1,187 @@
+/*
+ * Copyright (c) 2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include <cuco/hash_functions.cuh>
+#include <cuda/functional>
+#include <cuda/std/bit>
+#include <cuda/std/limits>
+
+#include <cstdint>
+#include <nv/target>
+
+namespace cuco {
+
+/**
+ * @brief A policy that defines how Arrow Block-Split Bloom Filter generates and stores a key's
+ * fingerprint.
+ *
+ * @note: This file is a part of cuCollections. Copied here until we get a cuco bump for cudf.
+ *
+ * Reference:
+ * https://github.com/apache/arrow/blob/be1dcdb96b030639c0b56955c4c62f9d6b03f473/cpp/src/parquet/bloom_filter.cc#L219-L230
+ *
+ * Example:
+ * @code{.cpp}
+ * template <typename KeyType, std::uint32_t NUM_FILTER_BLOCKS>
+ * void bulk_insert_and_eval_arrow_policy_bloom_filter(device_vector<KeyType> const& positive_keys,
+ *                                                 device_vector<KeyType> const& negative_keys)
+ * {
+ *     using policy_type = cuco::arrow_filter_policy<key_type>;
+ *
+ *     // Warn or throw if the number of filter blocks is greater than maximum used by Arrow policy.
+ *     static_assert(NUM_FILTER_BLOCKS <= policy_type::max_filter_blocks, "NUM_FILTER_BLOCKS must be
+ *                                                                         in range: [1, 4194304]");
+ *
+ *     // Create a bloom filter with Arrow policy
+ *     cuco::bloom_filter<key_type, cuco::extent<size_t>,
+ *         cuda::thread_scope_device, policy_type> filter{NUM_FILTER_BLOCKS};
+ *
+ *     // Add positive keys to the bloom filter
+ *     filter.add(positive_keys.begin(), positive_keys.end());
+ *
+ *     auto const num_tp = positive_keys.size();
+ *     auto const num_tn = negative_keys.size();
+ *
+ *     // Vectors to store query results.
+ *     thrust::device_vector<bool> true_positive_result(num_tp, false);
+ *     thrust::device_vector<bool> true_negative_result(num_tn, false);
+ *
+ *     // Query the bloom filter for the inserted keys.
+ *     filter.contains(positive_keys.begin(), positive_keys.end(), true_positive_result.begin());
+ *
+ *     // We should see a true-positive rate of 1.
+ *     float true_positive_rate = float(thrust::count(thrust::device,
+ *          true_positive_result.begin(), true_positive_result.end(), true)) / float(num_tp);
+ *
+ *     // Query the bloom filter for the non-inserted keys.
+ *     filter.contains(negative_keys.begin(), negative_keys.end(), true_negative_result.begin());
+ *
+ *     // We may see a false-positive rate > 0 depending on the number of bits in the
+ *     // filter and the number of hashes used per key.
+ *     float false_positive_rate = float(thrust::count(thrust::device,
+ *          true_negative_result.begin(), true_negative_result.end(), true)) / float(num_tn);
+ * }
+ * @endcode
+ *
+ * @tparam Key The type of the values to generate a fingerprint for.
+ */
+template <class Key, class Hash>
+class arrow_filter_policy {
+ public:
+  using hasher             = Hash;           ///< Hash function for Arrow bloom filter policy
+  using word_type          = std::uint32_t;  ///< uint32_t for Arrow bloom filter policy
+  using hash_argument_type = typename hasher::argument_type;  ///< Hash function input type
+  using hash_result_type   = decltype(std::declval<hasher>()(
+    std::declval<hash_argument_type>()));  ///< hash function output type
+
+  static constexpr uint32_t bits_set_per_block = 8;  ///< hardcoded bits set per Arrow filter block
+  static constexpr uint32_t words_per_block    = 8;  ///< hardcoded words per Arrow filter block
+
+  static constexpr std::uint32_t bytes_per_filter_block =
+    32;  ///< Number of bytes in one Arrow filter block
+  static constexpr std::uint32_t max_arrow_filter_bytes =
+    128 * 1024 * 1024;  ///< Max bytes in Arrow bloom filter
+  static constexpr std::uint32_t max_filter_blocks =
+    (max_arrow_filter_bytes /
+     bytes_per_filter_block);  ///< Max sub-filter blocks allowed in Arrow bloom filter
+
+ private:
+  // Arrow's block-based bloom filter algorithm needs these eight odd SALT values to calculate
+  // eight indexes of bit to set, one bit in each 32-bit (uint32_t) word.
+  __device__ static constexpr cuda::std::array<std::uint32_t, 8> SALT()
+  {
+    return {0x47b6137bU,
+            0x44974d91U,
+            0x8824ad5bU,
+            0xa2b7289dU,
+            0x705495c7U,
+            0x2df1424bU,
+            0x9efc4947U,
+            0x5c6bfb31U};
+  }
+
+ public:
+  /**
+   * @brief Constructs the `arrow_filter_policy` object.
+   *
+   * @note The number of filter blocks with Arrow policy must be in the
+   * range of [1, 4194304]. If the bloom filter is constructed with a larger
+   * number of blocks, only the first 4194304 (128MB) blocks will be used.
+   *
+   * @param hash Hash function used to generate a key's fingerprint
+   */
+  __host__ __device__ constexpr arrow_filter_policy(hasher hash = {}) : hash_{hash} {}
+
+  /**
+   * @brief Generates the hash value for a given key.
+   *
+   * @param key The key to hash
+   *
+   * @return The hash value of the key
+   */
+  __device__ constexpr hash_result_type hash(hash_argument_type const& key) const
+  {
+    return hash_(key);
+  }
+
+  /**
+   * @brief Determines the filter block a key is added into.
+   *
+   * @note The number of filter blocks with Arrow policy must be in the
+   * range of [1, 4194304]. Passing a larger `num_blocks` will still
+   * upperbound the number of blocks used to the mentioned range.
+   *
+   * @tparam Extent Size type that is used to determine the number of blocks in the filter
+   *
+   * @param hash Hash value of the key
+   * @param num_blocks Number of block in the filter
+   *
+   * @return The block index for the given key's hash value
+   */
+  template <class Extent>
+  __device__ constexpr auto block_index(hash_result_type hash, Extent num_blocks) const
+  {
+    constexpr auto hash_bits = cuda::std::numeric_limits<word_type>::digits;
+    // TODO: assert if num_blocks > max_filter_blocks
+    auto const max_blocks = cuda::std::min<Extent>(num_blocks, max_filter_blocks);
+    // Make sure we are only contained withing the `max_filter_blocks` blocks
+    return static_cast<word_type>(((hash >> hash_bits) * max_blocks) >> hash_bits) % max_blocks;
+  }
+
+  /**
+   * @brief Determines the fingerprint pattern for a word/segment within the filter block for a
+   * given key's hash value.
+   *
+   * @param hash Hash value of the key
+   * @param word_index Target word/segment within the filter block
+   *
+   * @return The bit pattern for the word/segment in the filter block
+   */
+  __device__ constexpr word_type word_pattern(hash_result_type hash, std::uint32_t word_index) const
+  {
+    // SALT array to calculate bit indexes for the current word
+    auto constexpr salt = SALT();
+    word_type const key = static_cast<word_type>(hash);
+    return word_type{1} << ((key * salt[word_index]) >> 27);
+  }
+
+ private:
+  hasher hash_;
+};
+
+}  // namespace cuco
\ No newline at end of file
diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 89f448de05f..5178fbba3c1 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -14,6 +14,7 @@
  * limitations under the License.
  */
 
+#include "arrow_filter_policy.cuh"
 #include "compact_protocol_reader.hpp"
 #include "io/parquet/parquet.hpp"
 #include "reader_impl_helpers.hpp"
@@ -36,6 +37,7 @@
 #include <cuco/bloom_filter_policy.cuh>
 #include <cuco/bloom_filter_ref.cuh>
 #include <cuco/hash_functions.cuh>
+#include <cuda/std/span>
 #include <thrust/for_each.h>
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/sequence.h>
@@ -48,6 +50,61 @@
 namespace cudf::io::parquet::detail {
 
 namespace {
+
+/**
+ * @brief Temporary function that tests for key `third-037493` in bloom filters of column `c2` in
+ * test Parquet file.
+ *
+ * @param buffer Device buffer containing bloom filter bitset
+ * @param chunk Current row group index
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ *
+ */
+void check_arbitrary_string_key(rmm::device_buffer const& buffer,
+                                size_t chunk,
+                                rmm::cuda_stream_view stream)
+{
+  using word_type   = cuda::std::uint32_t;
+  using key_type    = cuda::std::span<cuda::std::byte>;
+  using policy_type = cuco::arrow_filter_policy<key_type, cuco::xxhash_64<key_type>>;
+
+  thrust::for_each(
+    rmm::exec_policy_nosync(stream),
+    thrust::make_counting_iterator(0),
+    thrust::make_counting_iterator(1),
+    [bitset     = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data())),
+     num_blocks = static_cast<cuda::std::size_t>(buffer.size()) / sizeof(uint32_t),
+     chunk      = chunk,
+     stream     = stream] __device__(auto idx) {
+      // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
+      cuco::bloom_filter_ref<key_type,
+                             cuco::extent<std::size_t>,
+                             cuco::thread_scope_device,
+                             policy_type>
+        filter{
+          bitset,
+          num_blocks,
+          {},  // scope
+          {0}  // policy
+        };
+
+      // literal to search
+      cudf::string_view literal("third-037493", sizeof("third-037493"));
+      // convert to a cuda::std::span key to search
+      cuda::std::span<cuda::std::byte> const key(
+        const_cast<cuda::std::byte*>(reinterpret_cast<cuda::std::byte const*>(literal.data())),
+        static_cast<cuda::std::size_t>(literal.length()));
+      // Search in the filter
+      if (filter.contains(key)) {
+        printf("YES: Filter chunk: %lu contains key: third-037493\n", chunk);
+      } else {
+        printf("NO: Filter chunk: %lu does not contain key: third-037493\n", chunk);
+      }
+    });
+
+  stream.synchronize_no_throw();
+}
+
 /**
  * @brief Asynchronously reads bloom filters to device.
  *
@@ -119,36 +176,8 @@ std::future<void> read_bloom_filters_async(
           bloom_filter_data[chunk] =
             rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
 
-          /* MH: Remove this
-          using word_type = uint32_t;
-
-          thrust::for_each(rmm::exec_policy(stream),
-                           thrust::make_counting_iterator(0),
-                           thrust::make_counting_iterator(1),
-                           [words = reinterpret_cast<word_type*>(bloom_filter_data[chunk].data()),
-                            num_blocks = bloom_filter_data[chunk].size() / sizeof(uint32_t),
-                            chunk      = chunk,
-                            stream     = stream] __device__(auto idx) {
-                             using key_type = cuda::std::string;
-                             using policy_type =
-                               cuco::bloom_filter_policy<cuco::xxhash_64<key_type>, std::uint32_t,
-          8>;
-                             // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
-                             cuco::bloom_filter_ref<key_type,
-                                                    cuco::extent<std::size_t>,
-                                                    cuco::thread_scope_device,
-                                                    policy_type>
-                               filter{words, size_t{num_blocks}, {}, {8}};
-                             // cuda::std::string key{"third-136666"};
-                             // filter.add("third-136666");
-
-                             cuco::xxhash_64<key_type> hasher{};
-                             cuda::std::array<char, 13> val{"third-136666"};
-                             auto hash =
-          hasher.compute_hash(reinterpret_cast<std::byte*>(val.data()), val.size()); if
-          (filter.contains(hash)) { printf("Filter chunk: %lu contains key: third-136666\n", chunk);
-                             }
-                           });*/
+          // MH: TODO: Temporary test. Remove me!!
+          check_arbitrary_string_key(bloom_filter_data[chunk], chunk, stream);
         }
         // Read the bitset from datasource.
         else {

From 3dff590adeb7255d93e7fd15e081c25e5401d0ca Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 21 Nov 2024 08:41:10 +0000
Subject: [PATCH 10/82] Successfully search bloom filter

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 148 ++++++++++++++++++----
 1 file changed, 124 insertions(+), 24 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 5178fbba3c1..3c0c906a448 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -22,22 +22,18 @@
 #include <cudf/ast/detail/expression_transformer.hpp>
 #include <cudf/ast/detail/operators.hpp>
 #include <cudf/ast/expressions.hpp>
-#include <cudf/column/column_factories.hpp>
 #include <cudf/detail/cuco_helpers.hpp>
-#include <cudf/detail/iterator.cuh>
 #include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
-#include <cudf/utilities/error.hpp>
+#include <cudf/hashing/detail/xxhash_64.cuh>
 
 #include <rmm/cuda_stream_view.hpp>
 #include <rmm/device_buffer.hpp>
 #include <rmm/device_vector.hpp>
 #include <rmm/exec_policy.hpp>
 
-#include <cuco/bloom_filter_policy.cuh>
+#include <cuco/bloom_filter.cuh>
 #include <cuco/bloom_filter_ref.cuh>
-#include <cuco/hash_functions.cuh>
-#include <cuda/std/span>
 #include <thrust/for_each.h>
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/sequence.h>
@@ -46,11 +42,115 @@
 #include <iterator>
 #include <numeric>
 #include <optional>
+#include <random>
 
 namespace cudf::io::parquet::detail {
 
 namespace {
 
+std::pair<std::vector<char>, std::vector<size_t>> generate_chars_and_offsets(size_t num_keys)
+{
+  static std::vector<std::string> const strings{"first",
+                                                "second",
+                                                "third",
+                                                "fourth",
+                                                "fifth",
+                                                "sixth",
+                                                "seventh",
+                                                "eighth",
+                                                "ninth",
+                                                "tenth",
+                                                "eleventh",
+                                                "twelfth",
+                                                "thirteenth",
+                                                "fourteenth",
+                                                "fifteenth",
+                                                "sixteenth",
+                                                "seventeenth",
+                                                "eighteenth"};
+
+  auto constexpr seed = 0xf00d;
+  /*static*/ std::mt19937 engine{seed};
+  /*static*/ std::uniform_int_distribution dist{};
+
+  std::vector<size_t> offsets(num_keys + 1);
+  std::vector<char> chars;
+  chars.reserve(12 * num_keys);  // 12 is the length of "seventeenth", the largest string
+  size_t offset = 0;
+  offsets[0]    = size_t{0};
+  std::generate_n(offsets.begin() + 1, num_keys, [&]() {
+    auto const& string  = strings[dist(engine) % strings.size()];
+    auto const char_ptr = const_cast<char*>(string.data());
+    chars.insert(chars.end(), char_ptr, char_ptr + string.length());
+    offset += string.length();
+    return offset;
+  });
+  return {std::move(chars), std::move(offsets)};
+}
+
+void validate_filter_bitwise(rmm::cuda_stream_view stream)
+{
+  std::size_t constexpr num_filter_blocks = 4;
+  std::size_t constexpr num_keys          = 50;
+
+  // Generate strings data
+  auto const [h_chars, h_offsets] = generate_chars_and_offsets(num_keys);
+  auto const mr                   = cudf::get_current_device_resource_ref();
+  auto d_chars                    = cudf::detail::make_device_uvector_async(h_chars, stream, mr);
+  auto d_offsets                  = cudf::detail::make_device_uvector_async(h_offsets, stream, mr);
+
+  rmm::device_uvector<cudf::string_view> d_keys(num_keys, stream);
+  thrust::transform(rmm::exec_policy_nosync(stream),
+                    thrust::make_counting_iterator<size_t>(0),
+                    thrust::make_counting_iterator<size_t>(num_keys),
+                    d_keys.begin(),
+                    [chars   = thrust::raw_pointer_cast(d_chars.data()),
+                     offsets = thrust::raw_pointer_cast(d_offsets.data())] __device__(auto idx) {
+                      return cudf::string_view{
+                        chars + offsets[idx],
+                        static_cast<cudf::size_type>(offsets[idx + 1] - offsets[idx])};
+                    });
+
+  using key_type    = cudf::string_view;
+  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
+  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+  using filter_type = cuco::bloom_filter<key_type,
+                                         cuco::extent<size_t>,
+                                         cuda::thread_scope_device,
+                                         policy_type,
+                                         cudf::detail::cuco_allocator<char>>;
+  // Spawn a bloom filter
+  filter_type filter{
+    num_filter_blocks,
+    cuco::thread_scope_device,
+    {hasher_type{0}},
+    cudf::detail::cuco_allocator<char>{rmm::mr::polymorphic_allocator<char>{}, stream},
+    stream};
+
+  // Add strings to the bloom filter
+  filter.add(d_keys.begin(), d_keys.end(), stream);
+
+  using word_type = filter_type::word_type;
+
+  // Number of words in the filter
+  size_t const num_words = filter.block_extent() * filter.words_per_block;
+
+  // Get the filter bitset words
+  cudf::device_span<word_type const> filter_bitset(filter.data(), num_words);
+  // Expected filter bitset words
+  rmm::device_vector<word_type> const expected_bitset{
+    4194306,    4194305,  2359296,   1073774592, 524544,     1024,       268443648,  8519680,
+    2147500040, 8421380,  269500416, 4202624,    8396802,    100665344,  2147747840, 5243136,
+    131146,     655364,   285345792, 134222340,  545390596,  2281717768, 51201,      41943553,
+    1619656708, 67441680, 8462730,   361220,     2216738864, 587333888,  4219272,    873463873};
+
+  CUDF_EXPECTS(thrust::equal(rmm::exec_policy(stream),
+                             expected_bitset.cbegin(),
+                             expected_bitset.cend(),
+                             filter_bitset.begin()),
+               "Bloom filter bitset mismatched");
+}
+
 /**
  * @brief Temporary function that tests for key `third-037493` in bloom filters of column `c2` in
  * test Parquet file.
@@ -64,16 +164,21 @@ void check_arbitrary_string_key(rmm::device_buffer const& buffer,
                                 size_t chunk,
                                 rmm::cuda_stream_view stream)
 {
-  using word_type   = cuda::std::uint32_t;
-  using key_type    = cuda::std::span<cuda::std::byte>;
-  using policy_type = cuco::arrow_filter_policy<key_type, cuco::xxhash_64<key_type>>;
+  using key_type    = cudf::string_view;
+  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
+  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+  using word_type   = policy_type::word_type;
+
+  auto constexpr word_size       = sizeof(word_type);
+  auto constexpr words_per_block = policy_type::words_per_block;
+  auto const num_filter_blocks   = buffer.size() / (word_size * words_per_block);
 
   thrust::for_each(
-    rmm::exec_policy_nosync(stream),
+    rmm::exec_policy(stream),
     thrust::make_counting_iterator(0),
     thrust::make_counting_iterator(1),
     [bitset     = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data())),
-     num_blocks = static_cast<cuda::std::size_t>(buffer.size()) / sizeof(uint32_t),
+     num_blocks = num_filter_blocks,
      chunk      = chunk,
      stream     = stream] __device__(auto idx) {
       // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
@@ -81,19 +186,13 @@ void check_arbitrary_string_key(rmm::device_buffer const& buffer,
                              cuco::extent<std::size_t>,
                              cuco::thread_scope_device,
                              policy_type>
-        filter{
-          bitset,
-          num_blocks,
-          {},  // scope
-          {0}  // policy
-        };
+        filter{bitset,
+               num_blocks,
+               {},  // scope
+               {hasher_type{0}}};
 
       // literal to search
-      cudf::string_view literal("third-037493", sizeof("third-037493"));
-      // convert to a cuda::std::span key to search
-      cuda::std::span<cuda::std::byte> const key(
-        const_cast<cuda::std::byte*>(reinterpret_cast<cuda::std::byte const*>(literal.data())),
-        static_cast<cuda::std::size_t>(literal.length()));
+      cudf::string_view key("third-037493", 12);
       // Search in the filter
       if (filter.contains(key)) {
         printf("YES: Filter chunk: %lu contains key: third-037493\n", chunk);
@@ -101,8 +200,6 @@ void check_arbitrary_string_key(rmm::device_buffer const& buffer,
         printf("NO: Filter chunk: %lu does not contain key: third-037493\n", chunk);
       }
     });
-
-  stream.synchronize_no_throw();
 }
 
 /**
@@ -206,6 +303,9 @@ std::future<void> read_bloom_filters_async(
     }
   };
 
+  // MH: Remove me. Bitwise validation for bloom filter
+  validate_filter_bitwise(stream);
+
   return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
 }
 

From 71e1d331f79ddef0521489f142527239836f6433 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 21 Nov 2024 19:03:22 +0000
Subject: [PATCH 11/82] style fix

---
 cpp/src/io/parquet/arrow_filter_policy.cuh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/arrow_filter_policy.cuh b/cpp/src/io/parquet/arrow_filter_policy.cuh
index 95edf68cab4..dfb6745bed8 100644
--- a/cpp/src/io/parquet/arrow_filter_policy.cuh
+++ b/cpp/src/io/parquet/arrow_filter_policy.cuh
@@ -184,4 +184,4 @@ class arrow_filter_policy {
   hasher hash_;
 };
 
-}  // namespace cuco
\ No newline at end of file
+}  // namespace cuco

From aa65a2bb58238c27a9f6d16fe714fe9e3c59dfd6 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Fri, 22 Nov 2024 02:35:00 +0000
Subject: [PATCH 12/82] Code cleanup

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 80 +++++++++++++----------
 1 file changed, 46 insertions(+), 34 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 3c0c906a448..6eed5c5dd21 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -34,8 +34,8 @@
 
 #include <cuco/bloom_filter.cuh>
 #include <cuco/bloom_filter_ref.cuh>
-#include <thrust/for_each.h>
 #include <thrust/iterator/counting_iterator.h>
+#include <thrust/logical.h>
 #include <thrust/sequence.h>
 
 #include <future>
@@ -155,51 +155,61 @@ void validate_filter_bitwise(rmm::cuda_stream_view stream)
  * @brief Temporary function that tests for key `third-037493` in bloom filters of column `c2` in
  * test Parquet file.
  *
+ * @tparam Key Type of the key to query bloom filter.
+ *
  * @param buffer Device buffer containing bloom filter bitset
  * @param chunk Current row group index
  * @param stream CUDA stream used for device memory operations and kernel launches
  *
  */
-void check_arbitrary_string_key(rmm::device_buffer const& buffer,
-                                size_t chunk,
-                                rmm::cuda_stream_view stream)
+template <typename Key = cudf::string_view>
+[[nodiscard]] bool check_arbitrary_string_key(rmm::device_buffer const& buffer,
+                                              Key const& literal,
+                                              size_t chunk_idx,
+                                              rmm::cuda_stream_view stream)
 {
-  using key_type    = cudf::string_view;
+  using key_type    = Key;
   using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
   using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
-  using word_type   = policy_type::word_type;
+  using word_type   = typename policy_type::word_type;
 
+  // Filter properties
   auto constexpr word_size       = sizeof(word_type);
   auto constexpr words_per_block = policy_type::words_per_block;
   auto const num_filter_blocks   = buffer.size() / (word_size * words_per_block);
 
-  thrust::for_each(
-    rmm::exec_policy(stream),
-    thrust::make_counting_iterator(0),
-    thrust::make_counting_iterator(1),
-    [bitset     = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data())),
-     num_blocks = num_filter_blocks,
-     chunk      = chunk,
-     stream     = stream] __device__(auto idx) {
-      // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
-      cuco::bloom_filter_ref<key_type,
-                             cuco::extent<std::size_t>,
-                             cuco::thread_scope_device,
-                             policy_type>
-        filter{bitset,
-               num_blocks,
-               {},  // scope
-               {hasher_type{0}}};
-
-      // literal to search
-      cudf::string_view key("third-037493", 12);
-      // Search in the filter
-      if (filter.contains(key)) {
-        printf("YES: Filter chunk: %lu contains key: third-037493\n", chunk);
-      } else {
-        printf("NO: Filter chunk: %lu does not contain key: third-037493\n", chunk);
-      }
-    });
+  // Bitset ptr must be a non-const to be used in bloom_filter_ref.
+  auto bitset = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data()));
+
+  // Create a bloom filter view
+  cuco::
+    bloom_filter_ref<key_type, cuco::extent<std::size_t>, cuco::thread_scope_device, policy_type>
+      filter{bitset,
+             num_filter_blocks,
+             {},  // scope
+             {hasher_type{0}}};
+
+  // Copy over the key (literal) to device
+  rmm::device_buffer d_key{literal.data(), static_cast<size_t>(literal.size_bytes()), stream};
+
+  // Query literal in bloom filter.
+  bool const is_literal_found =
+    thrust::count_if(rmm::exec_policy(stream),
+                     thrust::make_counting_iterator(0),
+                     thrust::make_counting_iterator(1),
+                     [filter   = filter,
+                      key_ptr  = reinterpret_cast<char*>(d_key.data()),
+                      key_size = static_cast<cudf::size_type>(d_key.size())] __device__(auto idx) {
+                       auto const d_key = cudf::string_view{key_ptr, key_size};
+                       return filter.contains(d_key);
+                     });
+
+  // MH: Temporary
+  auto const found_string = (is_literal_found) ? "YES" : "NO";
+  std::cout << "Literal: third-037493 found in chunk " << chunk_idx << ": " << found_string
+            << std::endl;
+
+  return is_literal_found;
 }
 
 /**
@@ -274,7 +284,9 @@ std::future<void> read_bloom_filters_async(
             rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
 
           // MH: TODO: Temporary test. Remove me!!
-          check_arbitrary_string_key(bloom_filter_data[chunk], chunk, stream);
+          cudf::string_view literal{"third-037493", 12};
+          std::ignore =
+            check_arbitrary_string_key(bloom_filter_data[chunk], literal, chunk, stream);
         }
         // Read the bitset from datasource.
         else {

From c52821b91db31380c4cfc570bb08ba0d1093ef57 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Mon, 25 Nov 2024 21:30:54 +0000
Subject: [PATCH 13/82] add tests

---
 cpp/tests/CMakeLists.txt               |  1 +
 cpp/tests/hashing/bloom_filter_test.cu | 95 ++++++++++++++++++++++++++
 2 files changed, 96 insertions(+)
 create mode 100644 cpp/tests/hashing/bloom_filter_test.cu

diff --git a/cpp/tests/CMakeLists.txt b/cpp/tests/CMakeLists.txt
index 666a7d4ba4b..219fafc6952 100644
--- a/cpp/tests/CMakeLists.txt
+++ b/cpp/tests/CMakeLists.txt
@@ -182,6 +182,7 @@ ConfigureTest(DATETIME_OPS_TEST datetime/datetime_ops_test.cpp)
 # * hashing tests ---------------------------------------------------------------------------------
 ConfigureTest(
   HASHING_TEST
+  hashing/bloom_filter_test.cu
   hashing/md5_test.cpp
   hashing/murmurhash3_x86_32_test.cpp
   hashing/murmurhash3_x64_128_test.cpp
diff --git a/cpp/tests/hashing/bloom_filter_test.cu b/cpp/tests/hashing/bloom_filter_test.cu
new file mode 100644
index 00000000000..e0e98dd84a0
--- /dev/null
+++ b/cpp/tests/hashing/bloom_filter_test.cu
@@ -0,0 +1,95 @@
+/*
+ * Copyright (c) 2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*
+#include <cudf_test/base_fixture.hpp>
+#include <cudf_test/column_utilities.hpp>
+#include <cudf_test/column_wrapper.hpp>
+#include <cudf_test/iterator_utilities.hpp>
+
+#include <cudf/detail/cuco_helpers.hpp>
+#include <cudf/hashing/detail/xxhash_64.cuh>
+#include <cudf/utilities/default_stream.hpp>
+
+#include <cuco/bloom_filter.cuh>
+
+using StringType = cudf::string_view;
+
+template <typename T>
+class BloomFilter_TestTyped : public cudf::test::BaseFixture {};
+
+TYPED_TEST_SUITE(BloomFilter_TestTyped, StringType);
+
+TYPED_TEST(BloomFilter_TestTyped, TestStrings)
+{
+  using key_type    = StringType;
+  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
+  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+
+  std::size_t constexpr num_filter_blocks = 4;
+  std::size_t constexpr num_keys          = 50;
+  auto stream                             = cudf::get_default_stream();
+
+  // strings data
+  auto data = cudf::test::strings_column_wrapper(
+    {"seventh",    "fifteenth",   "second",      "tenth",      "fifth",       "first",
+     "seventh",    "tenth",       "ninth",       "ninth",      "seventeenth", "eighteenth",
+     "thirteenth", "fifth",       "fourth",      "twelfth",    "second",      "second",
+     "fourth",     "seventh",     "seventh",     "tenth",      "thirteenth",  "seventeenth",
+     "fifth",      "seventeenth", "eighth",      "fourth",     "second",      "eighteenth",
+     "fifteenth",  "second",      "seventeenth", "thirteenth", "eighteenth",  "fifth",
+     "seventh",    "tenth",       "fourteenth",  "first",      "fifth",       "fifth",
+     "tenth",      "thirteenth",  "fourteenth",  "third",      "third",       "sixth",
+     "first",      "third"});
+  auto d_column = cudf::column_device_view::create(data);
+
+  // Spawn a bloom filter
+  cuco::bloom_filter<key_type,
+                     cuco::extent<size_t>,
+                     cuda::thread_scope_device,
+                     policy_type,
+                     cudf::detail::cuco_allocator<char>>
+    filter{num_filter_blocks,
+           cuco::thread_scope_device,
+           {hasher_type{0}},
+           cudf::detail::cuco_allocator<char>{rmm::mr::polymorphic_allocator<char>{}, stream},
+           stream};
+
+  // Add strings to the bloom filter
+  auto col = table.column(0);
+  filter.add(d_column->begin<key_type>(), d_column->end<key_type>(), stream);
+
+  // Number of words in the filter
+  cudf::size_type const num_words = filter.block_extent() * filter.words_per_block;
+
+  auto const output = cudf::column_view{
+    cudf::data_type{cudf::type_id::UINT32}, num_words, filter.data(), nullptr, 0, 0, {}};
+
+  using word_type = filter_type::word_type;
+
+  // Expected filter bitset words computed using Arrow implementation here:
+  // https://godbolt.org/z/oKfqcPWbY
+  auto expected = cudf::test::fixed_width_column_wrapper<word_type>(
+    {4194306,    4194305,  2359296,   1073774592, 524544,     1024,       268443648,  8519680,
+     2147500040, 8421380,  269500416, 4202624,    8396802,    100665344,  2147747840, 5243136,
+     131146,     655364,   285345792, 134222340,  545390596,  2281717768, 51201,      41943553,
+     1619656708, 67441680, 8462730,   361220,     2216738864, 587333888,  4219272,    873463873});
+  auto d_expected = cudf::column_device_view::create(expected);
+
+  // Check
+  CUDF_TEST_EXPECT_COLUMNS_EQUAL(output, d_expected);
+}
+*/
\ No newline at end of file

From 3a20a9814f60c08b893e9eb917d69f31672779c4 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 9 Nov 2024 00:11:28 +0000
Subject: [PATCH 14/82] Initial stuff for reading bloom filter from PQ files

---
 .../io/parquet/compact_protocol_reader.cpp    |  33 +++-
 .../io/parquet/compact_protocol_reader.hpp    |   4 +
 cpp/src/io/parquet/parquet.hpp                |  45 +++++
 .../io/parquet/reader_apply_bloom_filters.cu  |  36 ++++
 cpp/src/io/parquet/reader_impl_helpers.cpp    | 178 ++++++++++++++++++
 cpp/src/io/parquet/reader_impl_helpers.hpp    |  25 ++-
 cpp/src/io/parquet/reader_impl_preprocess.cu  |   3 +-
 7 files changed, 321 insertions(+), 3 deletions(-)
 create mode 100644 cpp/src/io/parquet/reader_apply_bloom_filters.cu

diff --git a/cpp/src/io/parquet/compact_protocol_reader.cpp b/cpp/src/io/parquet/compact_protocol_reader.cpp
index d276e946a51..55874822ade 100644
--- a/cpp/src/io/parquet/compact_protocol_reader.cpp
+++ b/cpp/src/io/parquet/compact_protocol_reader.cpp
@@ -655,6 +655,33 @@ void CompactProtocolReader::read(ColumnChunk* c)
   function_builder(this, op);
 }
 
+void CompactProtocolReader::read(BloomFilterAlgorithm* alg)
+{
+  auto op = std::make_tuple(parquet_field_union_enumerator(1, alg->algorithm));
+  function_builder(this, op);
+}
+
+void CompactProtocolReader::read(BloomFilterHash* hash)
+{
+  auto op = std::make_tuple(parquet_field_union_enumerator(1, hash->hash));
+  function_builder(this, op);
+}
+
+void CompactProtocolReader::read(BloomFilterCompression* comp)
+{
+  auto op = std::make_tuple(parquet_field_union_enumerator(1, comp->compression));
+  function_builder(this, op);
+}
+
+void CompactProtocolReader::read(BloomFilterHeader* bf)
+{
+  auto op = std::make_tuple(parquet_field_int32(1, bf->num_bytes),
+                            parquet_field_struct(2, bf->algorithm),
+                            parquet_field_struct(3, bf->hash),
+                            parquet_field_struct(4, bf->compression));
+  function_builder(this, op);
+}
+
 void CompactProtocolReader::read(ColumnChunkMetaData* c)
 {
   using optional_size_statistics =
@@ -662,7 +689,9 @@ void CompactProtocolReader::read(ColumnChunkMetaData* c)
   using optional_list_enc_stats =
     parquet_field_optional<std::vector<PageEncodingStats>,
                            parquet_field_struct_list<PageEncodingStats>>;
-  auto op = std::make_tuple(parquet_field_enum<Type>(1, c->type),
+  using optional_i64 = parquet_field_optional<int64_t, parquet_field_int64>;
+  using optional_i32 = parquet_field_optional<int32_t, parquet_field_int32>;
+  auto op            = std::make_tuple(parquet_field_enum<Type>(1, c->type),
                             parquet_field_enum_list(2, c->encodings),
                             parquet_field_string_list(3, c->path_in_schema),
                             parquet_field_enum<Compression>(4, c->codec),
@@ -674,6 +703,8 @@ void CompactProtocolReader::read(ColumnChunkMetaData* c)
                             parquet_field_int64(11, c->dictionary_page_offset),
                             parquet_field_struct(12, c->statistics),
                             optional_list_enc_stats(13, c->encoding_stats),
+                            optional_i64(14, c->bloom_filter_offset),
+                            optional_i32(15, c->bloom_filter_length),
                             optional_size_statistics(16, c->size_statistics));
   function_builder(this, op);
 }
diff --git a/cpp/src/io/parquet/compact_protocol_reader.hpp b/cpp/src/io/parquet/compact_protocol_reader.hpp
index b87f2e9c692..3d39daa60d1 100644
--- a/cpp/src/io/parquet/compact_protocol_reader.hpp
+++ b/cpp/src/io/parquet/compact_protocol_reader.hpp
@@ -108,6 +108,10 @@ class CompactProtocolReader {
   void read(IntType* t);
   void read(RowGroup* r);
   void read(ColumnChunk* c);
+  void read(BloomFilterAlgorithm* bf);
+  void read(BloomFilterHash* bf);
+  void read(BloomFilterCompression* bf);
+  void read(BloomFilterHeader* bf);
   void read(ColumnChunkMetaData* c);
   void read(PageHeader* p);
   void read(DataPageHeader* d);
diff --git a/cpp/src/io/parquet/parquet.hpp b/cpp/src/io/parquet/parquet.hpp
index 2851ef67a65..118ec43133b 100644
--- a/cpp/src/io/parquet/parquet.hpp
+++ b/cpp/src/io/parquet/parquet.hpp
@@ -382,12 +382,57 @@ struct ColumnChunkMetaData {
   // Set of all encodings used for pages in this column chunk. This information can be used to
   // determine if all data pages are dictionary encoded for example.
   std::optional<std::vector<PageEncodingStats>> encoding_stats;
+  // Byte offset from beginning of file to Bloom filter data.
+  std::optional<int64_t> bloom_filter_offset;
+  // Size of Bloom filter data including the serialized header, in bytes. Added in 2.10 so readers
+  // may not read this field from old files and it can be obtained after the BloomFilterHeader has
+  // been deserialized. Writers should write this field so readers can read the bloom filter in a
+  // single I/O.
+  std::optional<int32_t> bloom_filter_length;
   // Optional statistics to help estimate total memory when converted to in-memory representations.
   // The histograms contained in these statistics can also be useful in some cases for more
   // fine-grained nullability/list length filter pushdown.
   std::optional<SizeStatistics> size_statistics;
 };
 
+/**
+ * @brief The algorithm used in Bloom filter.
+ **/
+struct BloomFilterAlgorithm {
+  /** Block-based Bloom filter. **/
+  enum Algorithm { UNDEFINED, SPLIT_BLOCK };
+  Algorithm algorithm{Algorithm::SPLIT_BLOCK};
+};
+
+/**
+ * @brief The hash function used in Bloom filter. This function takes the hash of a column value
+ * using plain encoding.
+ **/
+struct BloomFilterHash {
+  /** xxHash Strategy. **/
+  enum Hash { UNDEFINED, XXHASH };
+  Hash hash{Hash::XXHASH};
+};
+
+/**
+ * @brief The compression used in the Bloom filter.
+ **/
+struct BloomFilterCompression {
+  enum Compression { UNDEFINED, UNCOMPRESSED };
+  Compression compression{Compression::UNCOMPRESSED};
+};
+
+struct BloomFilterHeader {
+  // The size of bitset in bytes
+  int32_t num_bytes;
+  // The algorithm for setting bits. *
+  BloomFilterAlgorithm algorithm;
+  // The hash function used for Bloom filter. *
+  BloomFilterHash hash;
+  // The compression used in the Bloom filter *
+  BloomFilterCompression compression;
+};
+
 /**
  * @brief Thrift-derived struct describing a chunk of data for a particular
  * column
diff --git a/cpp/src/io/parquet/reader_apply_bloom_filters.cu b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
new file mode 100644
index 00000000000..2d1c20ba48c
--- /dev/null
+++ b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
@@ -0,0 +1,36 @@
+/*
+ * Copyright (c) 2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/**
+ * @file bloom_filter_reader.cu
+ * @brief Bloom filter reader based row group filtration implementation
+ */
+
+#include "parquet.hpp"
+#include "parquet_common.hpp"
+
+#include <cudf/utilities/error.hpp>
+
+#include <cuco/bloom_filter.cuh>
+
+#include <algorithm>
+#include <cstddef>
+#include <functional>
+#include <optional>
+#include <tuple>
+
+// TODO: Implement this
+cuda::std::optional<std::vector<std::vector<cudf::size_type>>> apply_bloom_filters() { return {}; }
\ No newline at end of file
diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index a6562d33de2..b6348a3f897 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -25,11 +25,16 @@
 
 #include <cudf/detail/utilities/logger.hpp>
 
+#include <rmm/cuda_stream_view.hpp>
+#include <rmm/device_buffer.hpp>
+
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/iterator/zip_iterator.h>
 
 #include <functional>
+#include <future>
 #include <numeric>
+#include <optional>
 #include <regex>
 
 namespace cudf::io::parquet::detail {
@@ -1028,8 +1033,169 @@ std::vector<std::string> aggregate_reader_metadata::get_pandas_index_names() con
   return names;
 }
 
+/**
+ * @brief Asynchronously reads bloom filters to device.
+ *
+ * @param sources Dataset sources
+ * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
+ * @param chunks List of chunk indices to read
+ * @param bloom_filter_offsets Bloom filter offsets for all chunks
+ * @param bloom_filter_sizes Bloom filter sizes for all chunks
+ * @param chunk_source_map Association between each column chunk and its source
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ *
+ * @return A future object for reading synchronization
+ */
+std::future<void> read_bloom_filters_async(
+  host_span<std::unique_ptr<datasource> const> sources,
+  cudf::host_span<rmm::device_buffer> bloom_filter_data,
+  host_span<size_type const> chunks,
+  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
+  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
+  std::vector<size_type> const& chunk_source_map,
+  rmm::cuda_stream_view stream)
+{
+  // Transfer bloom filter data
+  std::vector<std::future<size_t>> read_tasks;
+
+  // FIXME: Do not read all chunks. Instead use a list of chunks to read.
+  for (auto chunk : chunks) {
+    // Read bloom filter if present
+    if (bloom_filter_offsets[chunk].has_value()) {
+      auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
+      // If Bloom filter size (header + bitset) is available, just read the entire thing.
+      // Else just read 256 bytes which will contain the entire header and may contain the
+      // entire bitset as well.
+      auto constexpr bloom_filter_header_size_guess = 256;
+      auto const initial_read_size =
+        bloom_filter_sizes[chunk].value_or(bloom_filter_header_size_guess);
+
+      // Read an initial buffer from source
+      auto& source = sources[chunk_source_map[chunk]];
+      auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
+
+      // Deserialize the Bloom filter header from the buffer.
+      BloomFilterHeader header;
+      CompactProtocolReader cp{buffer->data(), buffer->size()};
+      cp.read(&header);
+
+      // Bloom filter header size
+      auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
+      auto const bitset_size              = header.num_bytes;
+
+      // Check if we already read in the filter bitset in the initial read.
+      if (initial_read_size >= bloom_filter_header_size + bitset_size) {
+        bloom_filter_data[chunk] =
+          rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
+      }
+      // Read the bitset from datasource.
+      else {
+        auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
+        // Directly read to device if preferred
+        if (source->is_device_read_preferred(bitset_size)) {
+          bloom_filter_data[chunk] = rmm::device_buffer(bitset_size, stream);
+          auto future_read_size =
+            source->device_read_async(bitset_offset,
+                                      bitset_size,
+                                      static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
+                                      stream);
+
+          read_tasks.emplace_back(std::move(future_read_size));
+        } else {
+          buffer                   = source->host_read(bitset_offset, bitset_size);
+          bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
+        }
+      }
+    }
+  }
+  auto sync_fn = [](decltype(read_tasks) read_tasks) {
+    for (auto& task : read_tasks) {
+      task.wait();
+    }
+  };
+  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
+}
+
+std::optional<std::vector<std::vector<size_type>>>
+aggregate_reader_metadata::apply_bloom_filter_to_row_groups(
+  host_span<std::unique_ptr<datasource> const> sources,
+  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<data_type const> output_dtypes,
+  host_span<int const> output_column_schemas,
+  rmm::cuda_stream_view stream) const
+{
+  // Number of row groups after filter_row_groups().
+  auto const num_row_groups = std::accumulate(
+    row_group_indices.begin(), row_group_indices.end(), 0, [](auto& sum, auto const& rgis) {
+      return sum + rgis.size();
+    });
+  // Descriptors for all the chunks that make up the selected columns
+  auto const num_input_columns = output_dtypes.size();
+  auto const num_chunks        = num_row_groups * num_input_columns;
+
+  // Association between each column chunk and its source
+  std::vector<size_type> chunk_source_map(num_chunks);
+
+  // Keep track of column chunk file offsets
+  std::vector<std::optional<int64_t>> bloom_filter_offsets(num_chunks);
+  std::vector<std::optional<int32_t>> bloom_filter_sizes(num_chunks);
+
+  // List of chunks to read
+  std::vector<size_type> chunks_to_read{};
+  chunks_to_read.reserve(num_chunks);
+
+  size_type chunk_count = 0;
+
+  // FIXME: We don't need to read bloom filters for all chunks. Only the ones belonging to the
+  // columns of our interest (equality predicate).
+  // For all data sources
+  for (size_t rg_source_index = 0; rg_source_index < row_group_indices.size(); rg_source_index++) {
+    auto const& rg_index = row_group_indices[rg_source_index];
+    // For all row groups in a data source
+    for (auto const rgi : rg_index) {
+      // For all column chunks in a row group
+      for (size_t col_idx = 0; col_idx < output_dtypes.size(); col_idx++) {
+        auto const schema_idx = output_column_schemas[col_idx];
+        auto& col_meta        = get_column_metadata(rgi, rg_source_index, schema_idx);
+
+        // Bloom filter offsets and sizes
+        bloom_filter_offsets[chunk_count] = col_meta.bloom_filter_offset;
+        bloom_filter_sizes[chunk_count]   = col_meta.bloom_filter_length;
+        chunks_to_read.emplace_back(chunk_count);
+
+        // Map each column chunk to its column index and its source index
+        chunk_source_map[chunk_count] = rg_source_index;
+        chunk_count++;
+      }
+    }
+  }
+
+  // Do we have any bloom filters
+  if (std::any_of(bloom_filter_offsets.cbegin(),
+                  bloom_filter_offsets.cend(),
+                  [](auto const offset) { return offset.has_value(); })) {
+    // Initialize the vector of bloom filter data buffers
+    std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
+
+    // Wait on bloom filter read tasks
+    read_bloom_filters_async(sources,
+                             bloom_filter_data,
+                             chunks_to_read,
+                             bloom_filter_offsets,
+                             bloom_filter_sizes,
+                             chunk_source_map,
+                             stream)
+      .wait();
+
+    // Apply bloom filter to row groups
+    // return apply_bloom_filters();
+  }
+  return {};
+}
+
 std::tuple<int64_t, size_type, std::vector<row_group_info>, std::vector<size_t>>
 aggregate_reader_metadata::select_row_groups(
+  host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
   int64_t skip_rows_opt,
   std::optional<size_type> const& num_rows_opt,
@@ -1048,6 +1214,18 @@ aggregate_reader_metadata::select_row_groups(
         host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
     }
   }
+
+  // FIXME: Provide the actual condition for this if
+  if (true /* equality predicate provided */) {
+    filtered_row_group_indices = apply_bloom_filter_to_row_groups(
+      sources, row_group_indices, output_dtypes, output_column_schemas, stream);
+
+    if (filtered_row_group_indices.has_value()) {
+      row_group_indices =
+        host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
+    }
+  }
+
   std::vector<row_group_info> selection;
   auto [rows_to_skip, rows_to_read] = [&]() {
     if (not row_group_indices.empty()) { return std::pair<int64_t, size_type>{}; }
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index fd692c0cdd6..82228599cd4 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -343,6 +343,7 @@ class aggregate_reader_metadata {
    * The input `row_start` and `row_count` parameters will be recomputed and output as the valid
    * values based on the input row group list.
    *
+   * @param sources Lists of input datasources.
    * @param row_group_indices Lists of row groups to read, one per source
    * @param row_start Starting row of the selection
    * @param row_count Total number of rows selected
@@ -354,7 +355,8 @@ class aggregate_reader_metadata {
    *         starting row, and list of number of rows per source.
    */
   [[nodiscard]] std::tuple<int64_t, size_type, std::vector<row_group_info>, std::vector<size_t>>
-  select_row_groups(host_span<std::vector<size_type> const> row_group_indices,
+  select_row_groups(host_span<std::unique_ptr<datasource> const> sources,
+                    host_span<std::vector<size_type> const> row_group_indices,
                     int64_t row_start,
                     std::optional<size_type> const& row_count,
                     host_span<data_type const> output_dtypes,
@@ -362,6 +364,27 @@ class aggregate_reader_metadata {
                     std::optional<std::reference_wrapper<ast::expression const>> filter,
                     rmm::cuda_stream_view stream) const;
 
+  /**
+   * @brief Filters the row groups using bloom filters
+   *
+   * @param sources Dataset sources
+   * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
+   * @param begin_chunk Index of first column chunk to read
+   * @param end_chunk Index after the last column chunk to read
+   * @param bloom_filter_offsets Bloom filter offsets for all chunks
+   * @param bloom_filter_sizes Bloom filter sizes for all chunks
+   * @param chunk_source_map Association between each column chunk and its source
+   * @param stream CUDA stream used for device memory operations and kernel launches
+   *
+   * @return Filtered row group indices, if any is filtered.
+   */
+  std::optional<std::vector<std::vector<size_type>>> apply_bloom_filter_to_row_groups(
+    host_span<std::unique_ptr<datasource> const> sources,
+    host_span<std::vector<size_type> const> row_group_indices,
+    host_span<data_type const> output_dtypes,
+    host_span<int const> output_column_schemas,
+    rmm::cuda_stream_view stream) const;
+
   /**
    * @brief Filters and reduces down to a selection of columns
    *
diff --git a/cpp/src/io/parquet/reader_impl_preprocess.cu b/cpp/src/io/parquet/reader_impl_preprocess.cu
index bcdae4cbd3b..135ca56af89 100644
--- a/cpp/src/io/parquet/reader_impl_preprocess.cu
+++ b/cpp/src/io/parquet/reader_impl_preprocess.cu
@@ -1284,7 +1284,8 @@ void reader::impl::preprocess_file(read_mode mode)
            _file_itm_data.global_num_rows,
            _file_itm_data.row_groups,
            _file_itm_data.num_rows_per_source) =
-    _metadata->select_row_groups(_options.row_group_indices,
+    _metadata->select_row_groups(_sources,
+                                 _options.row_group_indices,
                                  _options.skip_rows,
                                  _options.num_rows,
                                  output_dtypes,

From d67e4b5dce291213da6d321acf8d28975302f17a Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 9 Nov 2024 00:22:21 +0000
Subject: [PATCH 15/82] Minor bug fix

---
 cpp/src/io/parquet/reader_impl_helpers.cpp | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index b6348a3f897..da000edfd04 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -1215,12 +1215,13 @@ aggregate_reader_metadata::select_row_groups(
     }
   }
 
-  // FIXME: Provide the actual condition for this if
+  // FIXME: Provide the actual condition for this
   if (true /* equality predicate provided */) {
-    filtered_row_group_indices = apply_bloom_filter_to_row_groups(
+    auto const bloom_filtered_row_groups = apply_bloom_filter_to_row_groups(
       sources, row_group_indices, output_dtypes, output_column_schemas, stream);
-
-    if (filtered_row_group_indices.has_value()) {
+    // TODO: Can use a better logic here.
+    if (bloom_filtered_row_groups.has_value()) {
+      filtered_row_group_indices.value() = std::move(bloom_filtered_row_groups.value());
       row_group_indices =
         host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
     }

From 10471d466ac3985feab08410a76c5e42b2f6f458 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 9 Nov 2024 00:22:55 +0000
Subject: [PATCH 16/82] Apply style fix

---
 cpp/src/io/parquet/reader_apply_bloom_filters.cu | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/reader_apply_bloom_filters.cu b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
index 2d1c20ba48c..fc85a0a1eb2 100644
--- a/cpp/src/io/parquet/reader_apply_bloom_filters.cu
+++ b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
@@ -33,4 +33,4 @@
 #include <tuple>
 
 // TODO: Implement this
-cuda::std::optional<std::vector<std::vector<cudf::size_type>>> apply_bloom_filters() { return {}; }
\ No newline at end of file
+cuda::std::optional<std::vector<std::vector<cudf::size_type>>> apply_bloom_filters() { return {}; }

From 1e12662ca1aa75a5a2d4c8ce894df2ef8b2117d8 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 16 Nov 2024 03:12:55 +0000
Subject: [PATCH 17/82] Some updates

---
 cpp/src/io/parquet/predicate_pushdown.cpp  | 14 +++++++
 cpp/src/io/parquet/reader_impl_helpers.cpp | 44 +++++++++++++---------
 cpp/src/io/parquet/reader_impl_helpers.hpp |  2 +
 3 files changed, 43 insertions(+), 17 deletions(-)

diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index cd3dcd2bce4..abc8978d8db 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -391,6 +391,7 @@ class stats_expression_converter : public ast::detail::expression_transformer {
 }  // namespace
 
 std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::filter_row_groups(
+  host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
   host_span<data_type const> output_dtypes,
   host_span<int const> output_column_schemas,
@@ -491,6 +492,19 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
     }
     filtered_row_group_indices.push_back(std::move(filtered_row_groups));
   }
+
+  // If equality predicate
+  if (true /* is_equality_predicate */) {
+    filtered_row_group_indices =
+      apply_bloom_filter_to_row_groups(
+        sources,
+        filtered_row_group_indices.empty() ? input_row_group_indices : filtered_row_group_indices,
+        output_dtypes,
+        output_column_schemas,
+        stream)
+        .value();
+  }
+
   return {std::move(filtered_row_group_indices)};
 }
 
diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index da000edfd04..7ca1ffc4253 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -1079,6 +1079,20 @@ std::future<void> read_bloom_filters_async(
       CompactProtocolReader cp{buffer->data(), buffer->size()};
       cp.read(&header);
 
+      // Test if header is valid.
+      auto const is_header_valid =
+        (header.num_bytes % 32) == 0 and
+        header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
+        header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
+        header.hash.hash == BloomFilterHash::Hash::XXHASH;
+
+      if (not is_header_valid) {
+        // Simply use an empty device buffer and move on.
+        bloom_filter_data[chunk] = rmm::device_buffer{};
+        CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
+        continue;
+      }
+
       // Bloom filter header size
       auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
       auto const bitset_size              = header.num_bytes;
@@ -1106,6 +1120,9 @@ std::future<void> read_bloom_filters_async(
           bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
         }
       }
+    } else {
+      // Simply use an empty device buffer.
+      bloom_filter_data[chunk] = rmm::device_buffer{};
     }
   }
   auto sync_fn = [](decltype(read_tasks) read_tasks) {
@@ -1124,11 +1141,16 @@ aggregate_reader_metadata::apply_bloom_filter_to_row_groups(
   host_span<int const> output_column_schemas,
   rmm::cuda_stream_view stream) const
 {
-  // Number of row groups after filter_row_groups().
-  auto const num_row_groups = std::accumulate(
-    row_group_indices.begin(), row_group_indices.end(), 0, [](auto& sum, auto const& rgis) {
-      return sum + rgis.size();
-    });
+  // Create row group indices.
+  // std::vector<std::vector<size_type>> filtered_row_group_indices;
+  // Number of total row groups to process.
+  auto const num_row_groups = std::accumulate(row_group_indices.begin(),
+                                              row_group_indices.end(),
+                                              0,
+                                              [](size_type sum, auto const& per_file_row_groups) {
+                                                return sum + per_file_row_groups.size();
+                                              });
+
   // Descriptors for all the chunks that make up the selected columns
   auto const num_input_columns = output_dtypes.size();
   auto const num_chunks        = num_row_groups * num_input_columns;
@@ -1215,18 +1237,6 @@ aggregate_reader_metadata::select_row_groups(
     }
   }
 
-  // FIXME: Provide the actual condition for this
-  if (true /* equality predicate provided */) {
-    auto const bloom_filtered_row_groups = apply_bloom_filter_to_row_groups(
-      sources, row_group_indices, output_dtypes, output_column_schemas, stream);
-    // TODO: Can use a better logic here.
-    if (bloom_filtered_row_groups.has_value()) {
-      filtered_row_group_indices.value() = std::move(bloom_filtered_row_groups.value());
-      row_group_indices =
-        host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
-    }
-  }
-
   std::vector<row_group_info> selection;
   auto [rows_to_skip, rows_to_read] = [&]() {
     if (not row_group_indices.empty()) { return std::pair<int64_t, size_type>{}; }
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 82228599cd4..7faae405b4a 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -323,6 +323,7 @@ class aggregate_reader_metadata {
   /**
    * @brief Filters the row groups based on predicate filter
    *
+   * @param sources Lists of input datasources.
    * @param row_group_indices Lists of row groups to read, one per source
    * @param output_dtypes Datatypes of of output columns
    * @param output_column_schemas schema indices of output columns
@@ -331,6 +332,7 @@ class aggregate_reader_metadata {
    * @return Filtered row group indices, if any is filtered.
    */
   [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> filter_row_groups(
+    host_span<std::unique_ptr<datasource> const> sources,
     host_span<std::vector<size_type> const> row_group_indices,
     host_span<data_type const> output_dtypes,
     host_span<int const> output_column_schemas,

From ee7217ca59649d75b6d4fb465e5e92257121626e Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 16 Nov 2024 05:04:13 +0000
Subject: [PATCH 18/82] Move contents to a separate file

---
 cpp/src/io/parquet/bloom_filter_reader.cpp | 209 +++++++++++++++++++++
 cpp/src/io/parquet/predicate_pushdown.cpp  |  12 --
 cpp/src/io/parquet/reader_impl_helpers.cpp | 184 +-----------------
 cpp/src/io/parquet/reader_impl_helpers.hpp |  19 +-
 4 files changed, 218 insertions(+), 206 deletions(-)
 create mode 100644 cpp/src/io/parquet/bloom_filter_reader.cpp

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cpp b/cpp/src/io/parquet/bloom_filter_reader.cpp
new file mode 100644
index 00000000000..346ccd22c58
--- /dev/null
+++ b/cpp/src/io/parquet/bloom_filter_reader.cpp
@@ -0,0 +1,209 @@
+/*
+ * Copyright (c) 2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "compact_protocol_reader.hpp"
+#include "io/parquet/parquet.hpp"
+#include "reader_impl_helpers.hpp"
+
+#include <cudf/detail/utilities/logger.hpp>
+
+#include <rmm/cuda_stream_view.hpp>
+#include <rmm/device_buffer.hpp>
+
+#include <thrust/iterator/counting_iterator.h>
+
+#include <future>
+#include <numeric>
+#include <optional>
+
+namespace cudf::io::parquet::detail {
+
+namespace {
+/**
+ * @brief Asynchronously reads bloom filters to device.
+ *
+ * @param sources Dataset sources
+ * @param num_chunks Number of total column chunks to read
+ * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
+ * @param bloom_filter_offsets Bloom filter offsets for all chunks
+ * @param bloom_filter_sizes Bloom filter sizes for all chunks
+ * @param chunk_source_map Association between each column chunk and its source
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ *
+ * @return A future object for reading synchronization
+ */
+std::future<void> read_bloom_filters_async(
+  host_span<std::unique_ptr<datasource> const> sources,
+  size_t num_chunks,
+  cudf::host_span<rmm::device_buffer> bloom_filter_data,
+  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
+  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
+  std::vector<size_type> const& chunk_source_map,
+  rmm::cuda_stream_view stream)
+{
+  // Read tasks for bloom filter data
+  std::vector<std::future<size_t>> read_tasks;
+
+  // Read bloom filters for all column chunks
+  std::for_each(
+    thrust::make_counting_iterator<size_t>(0),
+    thrust::make_counting_iterator<size_t>(num_chunks),
+    [&](auto const chunk) {
+      // Read bloom filter if present
+      if (bloom_filter_offsets[chunk].has_value()) {
+        auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
+        // If Bloom filter size (header + bitset) is available, just read the entire thing.
+        // Else just read 256 bytes which will contain the entire header and may contain the
+        // entire bitset as well.
+        auto constexpr bloom_filter_header_size_guess = 256;
+        auto const initial_read_size =
+          bloom_filter_sizes[chunk].value_or(bloom_filter_header_size_guess);
+
+        // Read an initial buffer from source
+        auto& source = sources[chunk_source_map[chunk]];
+        auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
+
+        // Deserialize the Bloom filter header from the buffer.
+        BloomFilterHeader header;
+        CompactProtocolReader cp{buffer->data(), buffer->size()};
+        cp.read(&header);
+
+        // Test if header is valid.
+        auto const is_header_valid =
+          (header.num_bytes % 32) == 0 and
+          header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
+          header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
+          header.hash.hash == BloomFilterHash::Hash::XXHASH;
+
+        // Do not read if the bloom filter is invalid
+        if (not is_header_valid) {
+          CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
+          return;
+        }
+
+        // Bloom filter header size
+        auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
+        auto const bitset_size              = header.num_bytes;
+
+        // Check if we already read in the filter bitset in the initial read.
+        if (initial_read_size >= bloom_filter_header_size + bitset_size) {
+          bloom_filter_data[chunk] =
+            rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
+        }
+        // Read the bitset from datasource.
+        else {
+          auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
+          // Directly read to device if preferred
+          if (source->is_device_read_preferred(bitset_size)) {
+            bloom_filter_data[chunk] = rmm::device_buffer(bitset_size, stream);
+            auto future_read_size =
+              source->device_read_async(bitset_offset,
+                                        bitset_size,
+                                        static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
+                                        stream);
+
+            read_tasks.emplace_back(std::move(future_read_size));
+          } else {
+            buffer                   = source->host_read(bitset_offset, bitset_size);
+            bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
+          }
+        }
+      }
+    });
+  auto sync_fn = [](decltype(read_tasks) read_tasks) {
+    for (auto& task : read_tasks) {
+      task.wait();
+    }
+  };
+  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
+}
+
+}  // namespace
+
+std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
+  host_span<std::unique_ptr<datasource> const> sources,
+  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<int const> column_schemas,
+  rmm::cuda_stream_view stream) const
+{
+  // Number of total row groups to process.
+  auto const num_row_groups = std::accumulate(
+    row_group_indices.begin(),
+    row_group_indices.end(),
+    size_t{0},
+    [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
+
+  // Descriptors for all the chunks that make up the selected columns
+  auto const num_input_columns = column_schemas.size();
+  auto const num_chunks        = num_row_groups * num_input_columns;
+
+  // Association between each column chunk and its source
+  std::vector<size_type> chunk_source_map(num_chunks);
+
+  // Keep track of column chunk file offsets
+  std::vector<std::optional<int64_t>> bloom_filter_offsets(num_chunks);
+  std::vector<std::optional<int32_t>> bloom_filter_sizes(num_chunks);
+
+  // Gather all bloom filter offsets and sizes.
+  size_type chunk_count = 0;
+
+  // For all data sources
+  std::for_each(thrust::make_counting_iterator<size_t>(0),
+                thrust::make_counting_iterator(row_group_indices.size()),
+                [&](auto const src_index) {
+                  // Get all row group indices in the data source
+                  auto const& rg_indices = row_group_indices[src_index];
+                  // For all row groups
+                  std::for_each(rg_indices.cbegin(), rg_indices.cend(), [&](auto const rg_index) {
+                    // For all column chunks
+                    std::for_each(
+                      column_schemas.begin(), column_schemas.end(), [&](auto const schema_idx) {
+                        auto& col_meta = get_column_metadata(rg_index, src_index, schema_idx);
+
+                        // Get bloom filter offsets and sizes
+                        bloom_filter_offsets[chunk_count] = col_meta.bloom_filter_offset;
+                        bloom_filter_sizes[chunk_count]   = col_meta.bloom_filter_length;
+
+                        // Map each column chunk to its source index
+                        chunk_source_map[chunk_count] = src_index;
+                        chunk_count++;
+                      });
+                  });
+                });
+
+  // Do we have any bloom filters
+  if (std::any_of(bloom_filter_offsets.cbegin(),
+                  bloom_filter_offsets.cend(),
+                  [](auto const offset) { return offset.has_value(); })) {
+    // Create a vector to store bloom filter data
+    std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
+
+    // Wait on bloom filter read tasks
+    read_bloom_filters_async(sources,
+                             num_chunks,
+                             bloom_filter_data,
+                             bloom_filter_offsets,
+                             bloom_filter_sizes,
+                             chunk_source_map,
+                             stream)
+      .wait();
+    // Return the vector
+    return bloom_filter_data;
+  }
+  return {};
+}
+
+}  // namespace cudf::io::parquet::detail
\ No newline at end of file
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index abc8978d8db..a977cfdeca7 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -493,18 +493,6 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
     filtered_row_group_indices.push_back(std::move(filtered_row_groups));
   }
 
-  // If equality predicate
-  if (true /* is_equality_predicate */) {
-    filtered_row_group_indices =
-      apply_bloom_filter_to_row_groups(
-        sources,
-        filtered_row_group_indices.empty() ? input_row_group_indices : filtered_row_group_indices,
-        output_dtypes,
-        output_column_schemas,
-        stream)
-        .value();
-  }
-
   return {std::move(filtered_row_group_indices)};
 }
 
diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index 7ca1ffc4253..9c05009b528 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -1033,188 +1033,6 @@ std::vector<std::string> aggregate_reader_metadata::get_pandas_index_names() con
   return names;
 }
 
-/**
- * @brief Asynchronously reads bloom filters to device.
- *
- * @param sources Dataset sources
- * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
- * @param chunks List of chunk indices to read
- * @param bloom_filter_offsets Bloom filter offsets for all chunks
- * @param bloom_filter_sizes Bloom filter sizes for all chunks
- * @param chunk_source_map Association between each column chunk and its source
- * @param stream CUDA stream used for device memory operations and kernel launches
- *
- * @return A future object for reading synchronization
- */
-std::future<void> read_bloom_filters_async(
-  host_span<std::unique_ptr<datasource> const> sources,
-  cudf::host_span<rmm::device_buffer> bloom_filter_data,
-  host_span<size_type const> chunks,
-  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
-  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
-  std::vector<size_type> const& chunk_source_map,
-  rmm::cuda_stream_view stream)
-{
-  // Transfer bloom filter data
-  std::vector<std::future<size_t>> read_tasks;
-
-  // FIXME: Do not read all chunks. Instead use a list of chunks to read.
-  for (auto chunk : chunks) {
-    // Read bloom filter if present
-    if (bloom_filter_offsets[chunk].has_value()) {
-      auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
-      // If Bloom filter size (header + bitset) is available, just read the entire thing.
-      // Else just read 256 bytes which will contain the entire header and may contain the
-      // entire bitset as well.
-      auto constexpr bloom_filter_header_size_guess = 256;
-      auto const initial_read_size =
-        bloom_filter_sizes[chunk].value_or(bloom_filter_header_size_guess);
-
-      // Read an initial buffer from source
-      auto& source = sources[chunk_source_map[chunk]];
-      auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
-
-      // Deserialize the Bloom filter header from the buffer.
-      BloomFilterHeader header;
-      CompactProtocolReader cp{buffer->data(), buffer->size()};
-      cp.read(&header);
-
-      // Test if header is valid.
-      auto const is_header_valid =
-        (header.num_bytes % 32) == 0 and
-        header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
-        header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
-        header.hash.hash == BloomFilterHash::Hash::XXHASH;
-
-      if (not is_header_valid) {
-        // Simply use an empty device buffer and move on.
-        bloom_filter_data[chunk] = rmm::device_buffer{};
-        CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
-        continue;
-      }
-
-      // Bloom filter header size
-      auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
-      auto const bitset_size              = header.num_bytes;
-
-      // Check if we already read in the filter bitset in the initial read.
-      if (initial_read_size >= bloom_filter_header_size + bitset_size) {
-        bloom_filter_data[chunk] =
-          rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
-      }
-      // Read the bitset from datasource.
-      else {
-        auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
-        // Directly read to device if preferred
-        if (source->is_device_read_preferred(bitset_size)) {
-          bloom_filter_data[chunk] = rmm::device_buffer(bitset_size, stream);
-          auto future_read_size =
-            source->device_read_async(bitset_offset,
-                                      bitset_size,
-                                      static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
-                                      stream);
-
-          read_tasks.emplace_back(std::move(future_read_size));
-        } else {
-          buffer                   = source->host_read(bitset_offset, bitset_size);
-          bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
-        }
-      }
-    } else {
-      // Simply use an empty device buffer.
-      bloom_filter_data[chunk] = rmm::device_buffer{};
-    }
-  }
-  auto sync_fn = [](decltype(read_tasks) read_tasks) {
-    for (auto& task : read_tasks) {
-      task.wait();
-    }
-  };
-  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
-}
-
-std::optional<std::vector<std::vector<size_type>>>
-aggregate_reader_metadata::apply_bloom_filter_to_row_groups(
-  host_span<std::unique_ptr<datasource> const> sources,
-  host_span<std::vector<size_type> const> row_group_indices,
-  host_span<data_type const> output_dtypes,
-  host_span<int const> output_column_schemas,
-  rmm::cuda_stream_view stream) const
-{
-  // Create row group indices.
-  // std::vector<std::vector<size_type>> filtered_row_group_indices;
-  // Number of total row groups to process.
-  auto const num_row_groups = std::accumulate(row_group_indices.begin(),
-                                              row_group_indices.end(),
-                                              0,
-                                              [](size_type sum, auto const& per_file_row_groups) {
-                                                return sum + per_file_row_groups.size();
-                                              });
-
-  // Descriptors for all the chunks that make up the selected columns
-  auto const num_input_columns = output_dtypes.size();
-  auto const num_chunks        = num_row_groups * num_input_columns;
-
-  // Association between each column chunk and its source
-  std::vector<size_type> chunk_source_map(num_chunks);
-
-  // Keep track of column chunk file offsets
-  std::vector<std::optional<int64_t>> bloom_filter_offsets(num_chunks);
-  std::vector<std::optional<int32_t>> bloom_filter_sizes(num_chunks);
-
-  // List of chunks to read
-  std::vector<size_type> chunks_to_read{};
-  chunks_to_read.reserve(num_chunks);
-
-  size_type chunk_count = 0;
-
-  // FIXME: We don't need to read bloom filters for all chunks. Only the ones belonging to the
-  // columns of our interest (equality predicate).
-  // For all data sources
-  for (size_t rg_source_index = 0; rg_source_index < row_group_indices.size(); rg_source_index++) {
-    auto const& rg_index = row_group_indices[rg_source_index];
-    // For all row groups in a data source
-    for (auto const rgi : rg_index) {
-      // For all column chunks in a row group
-      for (size_t col_idx = 0; col_idx < output_dtypes.size(); col_idx++) {
-        auto const schema_idx = output_column_schemas[col_idx];
-        auto& col_meta        = get_column_metadata(rgi, rg_source_index, schema_idx);
-
-        // Bloom filter offsets and sizes
-        bloom_filter_offsets[chunk_count] = col_meta.bloom_filter_offset;
-        bloom_filter_sizes[chunk_count]   = col_meta.bloom_filter_length;
-        chunks_to_read.emplace_back(chunk_count);
-
-        // Map each column chunk to its column index and its source index
-        chunk_source_map[chunk_count] = rg_source_index;
-        chunk_count++;
-      }
-    }
-  }
-
-  // Do we have any bloom filters
-  if (std::any_of(bloom_filter_offsets.cbegin(),
-                  bloom_filter_offsets.cend(),
-                  [](auto const offset) { return offset.has_value(); })) {
-    // Initialize the vector of bloom filter data buffers
-    std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
-
-    // Wait on bloom filter read tasks
-    read_bloom_filters_async(sources,
-                             bloom_filter_data,
-                             chunks_to_read,
-                             bloom_filter_offsets,
-                             bloom_filter_sizes,
-                             chunk_source_map,
-                             stream)
-      .wait();
-
-    // Apply bloom filter to row groups
-    // return apply_bloom_filters();
-  }
-  return {};
-}
-
 std::tuple<int64_t, size_type, std::vector<row_group_info>, std::vector<size_t>>
 aggregate_reader_metadata::select_row_groups(
   host_span<std::unique_ptr<datasource> const> sources,
@@ -1230,7 +1048,7 @@ aggregate_reader_metadata::select_row_groups(
   // if filter is not empty, then gather row groups to read after predicate pushdown
   if (filter.has_value()) {
     filtered_row_group_indices = filter_row_groups(
-      row_group_indices, output_dtypes, output_column_schemas, filter.value(), stream);
+      sources, row_group_indices, output_dtypes, output_column_schemas, filter.value(), stream);
     if (filtered_row_group_indices.has_value()) {
       row_group_indices =
         host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 7faae405b4a..b03aa9ec296 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -367,24 +367,21 @@ class aggregate_reader_metadata {
                     rmm::cuda_stream_view stream) const;
 
   /**
-   * @brief Filters the row groups using bloom filters
+   * @brief Reads bloom filter bitsets for the specified columns from the given lists of row
+   * groups.
    *
    * @param sources Dataset sources
-   * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
-   * @param begin_chunk Index of first column chunk to read
-   * @param end_chunk Index after the last column chunk to read
-   * @param bloom_filter_offsets Bloom filter offsets for all chunks
-   * @param bloom_filter_sizes Bloom filter sizes for all chunks
-   * @param chunk_source_map Association between each column chunk and its source
+   * @param row_group_indices Lists of row groups to read bloom filters from, one per source
+   * @param column_schemas Schema indices of columns whose bloom filters will be read
    * @param stream CUDA stream used for device memory operations and kernel launches
    *
-   * @return Filtered row group indices, if any is filtered.
+   * @return A list of bloom filter bitset device buffers flattened over column schemas over lists
+   * of row group indices
    */
-  std::optional<std::vector<std::vector<size_type>>> apply_bloom_filter_to_row_groups(
+  std::vector<rmm::device_buffer> read_bloom_filters(
     host_span<std::unique_ptr<datasource> const> sources,
     host_span<std::vector<size_type> const> row_group_indices,
-    host_span<data_type const> output_dtypes,
-    host_span<int const> output_column_schemas,
+    host_span<int const> column_schemas,
     rmm::cuda_stream_view stream) const;
 
   /**

From f8e6159e16d09e9c028f996c634ba9069d7c990e Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 16 Nov 2024 05:06:19 +0000
Subject: [PATCH 19/82] Revert erroneous changes

---
 .../io/parquet/reader_apply_bloom_filters.cu  | 36 -------------------
 cpp/src/io/parquet/reader_impl_helpers.cpp    |  5 ---
 2 files changed, 41 deletions(-)
 delete mode 100644 cpp/src/io/parquet/reader_apply_bloom_filters.cu

diff --git a/cpp/src/io/parquet/reader_apply_bloom_filters.cu b/cpp/src/io/parquet/reader_apply_bloom_filters.cu
deleted file mode 100644
index fc85a0a1eb2..00000000000
--- a/cpp/src/io/parquet/reader_apply_bloom_filters.cu
+++ /dev/null
@@ -1,36 +0,0 @@
-/*
- * Copyright (c) 2024, NVIDIA CORPORATION.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-/**
- * @file bloom_filter_reader.cu
- * @brief Bloom filter reader based row group filtration implementation
- */
-
-#include "parquet.hpp"
-#include "parquet_common.hpp"
-
-#include <cudf/utilities/error.hpp>
-
-#include <cuco/bloom_filter.cuh>
-
-#include <algorithm>
-#include <cstddef>
-#include <functional>
-#include <optional>
-#include <tuple>
-
-// TODO: Implement this
-cuda::std::optional<std::vector<std::vector<cudf::size_type>>> apply_bloom_filters() { return {}; }
diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index 9c05009b528..ae720a9622d 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -25,16 +25,11 @@
 
 #include <cudf/detail/utilities/logger.hpp>
 
-#include <rmm/cuda_stream_view.hpp>
-#include <rmm/device_buffer.hpp>
-
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/iterator/zip_iterator.h>
 
 #include <functional>
-#include <future>
 #include <numeric>
-#include <optional>
 #include <regex>
 
 namespace cudf::io::parquet::detail {

From 1886cabae52f2495e6b6071a15101f9c57b9d1a5 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 16 Nov 2024 05:13:54 +0000
Subject: [PATCH 20/82] Style and doc fix

---
 cpp/src/io/parquet/bloom_filter_reader.cpp |  2 +-
 cpp/src/io/parquet/parquet.hpp             | 29 +++++++++++++---------
 2 files changed, 18 insertions(+), 13 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cpp b/cpp/src/io/parquet/bloom_filter_reader.cpp
index 346ccd22c58..fabc70cc5f2 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cpp
+++ b/cpp/src/io/parquet/bloom_filter_reader.cpp
@@ -206,4 +206,4 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   return {};
 }
 
-}  // namespace cudf::io::parquet::detail
\ No newline at end of file
+}  // namespace cudf::io::parquet::detail
diff --git a/cpp/src/io/parquet/parquet.hpp b/cpp/src/io/parquet/parquet.hpp
index 118ec43133b..ff8e7a63486 100644
--- a/cpp/src/io/parquet/parquet.hpp
+++ b/cpp/src/io/parquet/parquet.hpp
@@ -396,40 +396,45 @@ struct ColumnChunkMetaData {
 };
 
 /**
- * @brief The algorithm used in Bloom filter.
- **/
+ * @brief The algorithm used in bloom filter
+ */
 struct BloomFilterAlgorithm {
-  /** Block-based Bloom filter. **/
+  // Block-based Bloom filter.
   enum Algorithm { UNDEFINED, SPLIT_BLOCK };
   Algorithm algorithm{Algorithm::SPLIT_BLOCK};
 };
 
 /**
- * @brief The hash function used in Bloom filter. This function takes the hash of a column value
- * using plain encoding.
- **/
+ * @brief The hash function used in Bloom filter
+ */
 struct BloomFilterHash {
-  /** xxHash Strategy. **/
+  // xxHash_64
   enum Hash { UNDEFINED, XXHASH };
   Hash hash{Hash::XXHASH};
 };
 
 /**
- * @brief The compression used in the Bloom filter.
- **/
+ * @brief The compression used in the bloom filter
+ */
 struct BloomFilterCompression {
   enum Compression { UNDEFINED, UNCOMPRESSED };
   Compression compression{Compression::UNCOMPRESSED};
 };
 
+/**
+ * @brief Bloom filter header struct
+ *
+ * The bloom filter data of a column chunk stores this header at the beginning
+ * following by the filter bitset.
+ */
 struct BloomFilterHeader {
   // The size of bitset in bytes
   int32_t num_bytes;
-  // The algorithm for setting bits. *
+  // The algorithm for setting bits
   BloomFilterAlgorithm algorithm;
-  // The hash function used for Bloom filter. *
+  // The hash function used for bloom filter
   BloomFilterHash hash;
-  // The compression used in the Bloom filter *
+  // The compression used in the bloom filter
   BloomFilterCompression compression;
 };
 

From be228b31f7664c3d7bd12ce398c24e785b871400 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 19 Nov 2024 03:58:42 +0000
Subject: [PATCH 21/82] Get equality predicate col indices

---
 ...lter_reader.cpp => bloom_filter_reader.cu} | 189 ++++++++++++++++++
 cpp/src/io/parquet/predicate_pushdown.cpp     |   8 +-
 cpp/src/io/parquet/reader_impl_helpers.hpp    |  20 ++
 3 files changed, 216 insertions(+), 1 deletion(-)
 rename cpp/src/io/parquet/{bloom_filter_reader.cpp => bloom_filter_reader.cu} (51%)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cpp b/cpp/src/io/parquet/bloom_filter_reader.cu
similarity index 51%
rename from cpp/src/io/parquet/bloom_filter_reader.cpp
rename to cpp/src/io/parquet/bloom_filter_reader.cu
index fabc70cc5f2..89f448de05f 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cpp
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -18,14 +18,30 @@
 #include "io/parquet/parquet.hpp"
 #include "reader_impl_helpers.hpp"
 
+#include <cudf/ast/detail/expression_transformer.hpp>
+#include <cudf/ast/detail/operators.hpp>
+#include <cudf/ast/expressions.hpp>
+#include <cudf/column/column_factories.hpp>
+#include <cudf/detail/cuco_helpers.hpp>
+#include <cudf/detail/iterator.cuh>
+#include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
+#include <cudf/utilities/error.hpp>
 
 #include <rmm/cuda_stream_view.hpp>
 #include <rmm/device_buffer.hpp>
+#include <rmm/device_vector.hpp>
+#include <rmm/exec_policy.hpp>
 
+#include <cuco/bloom_filter_policy.cuh>
+#include <cuco/bloom_filter_ref.cuh>
+#include <cuco/hash_functions.cuh>
+#include <thrust/for_each.h>
 #include <thrust/iterator/counting_iterator.h>
+#include <thrust/sequence.h>
 
 #include <future>
+#include <iterator>
 #include <numeric>
 #include <optional>
 
@@ -102,6 +118,37 @@ std::future<void> read_bloom_filters_async(
         if (initial_read_size >= bloom_filter_header_size + bitset_size) {
           bloom_filter_data[chunk] =
             rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
+
+          /* MH: Remove this
+          using word_type = uint32_t;
+
+          thrust::for_each(rmm::exec_policy(stream),
+                           thrust::make_counting_iterator(0),
+                           thrust::make_counting_iterator(1),
+                           [words = reinterpret_cast<word_type*>(bloom_filter_data[chunk].data()),
+                            num_blocks = bloom_filter_data[chunk].size() / sizeof(uint32_t),
+                            chunk      = chunk,
+                            stream     = stream] __device__(auto idx) {
+                             using key_type = cuda::std::string;
+                             using policy_type =
+                               cuco::bloom_filter_policy<cuco::xxhash_64<key_type>, std::uint32_t,
+          8>;
+                             // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
+                             cuco::bloom_filter_ref<key_type,
+                                                    cuco::extent<std::size_t>,
+                                                    cuco::thread_scope_device,
+                                                    policy_type>
+                               filter{words, size_t{num_blocks}, {}, {8}};
+                             // cuda::std::string key{"third-136666"};
+                             // filter.add("third-136666");
+
+                             cuco::xxhash_64<key_type> hasher{};
+                             cuda::std::array<char, 13> val{"third-136666"};
+                             auto hash =
+          hasher.compute_hash(reinterpret_cast<std::byte*>(val.data()), val.size()); if
+          (filter.contains(hash)) { printf("Filter chunk: %lu contains key: third-136666\n", chunk);
+                             }
+                           });*/
         }
         // Read the bitset from datasource.
         else {
@@ -123,16 +170,158 @@ std::future<void> read_bloom_filters_async(
         }
       }
     });
+
   auto sync_fn = [](decltype(read_tasks) read_tasks) {
     for (auto& task : read_tasks) {
       task.wait();
     }
   };
+
   return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
 }
 
+/**
+ * @brief Collects column indices with an equality predicate in the AST expression.
+ * This is used in row group filtering based on bloom filters.
+ */
+class equality_predicate_converter : public ast::detail::expression_transformer {
+ public:
+  equality_predicate_converter(ast::expression const& expr, size_type const& num_columns)
+    : _num_columns{num_columns}
+  {
+    expr.accept(*this);
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::literal const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override
+  {
+    _equality_expr = std::reference_wrapper<ast::expression const>(expr);
+    return expr;
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override
+  {
+    CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
+                 "Equality AST supports only left table");
+    CUDF_EXPECTS(expr.get_column_index() < _num_columns,
+                 "Column index cannot be more than number of columns in the table");
+    _equality_expr = std::reference_wrapper<ast::expression const>(expr);
+    return expr;
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_name_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(
+    ast::column_name_reference const& expr) override
+  {
+    CUDF_FAIL("Column name reference is not supported in equality AST");
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override
+  {
+    using cudf::ast::ast_operator;
+    auto const operands = expr.get_operands();
+    auto const op       = expr.get_operator();
+
+    if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
+      // First operand should be column reference, second should be literal.
+      CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
+                   "Only binary operations are supported on column reference");
+      CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
+                   "Second operand of binary operation with column reference must be a literal");
+      v->accept(*this);
+      if (op == ast_operator::EQUAL) { equality_col_idx.emplace_back(v->get_column_index()); }
+    } else {
+      auto new_operands = visit_operands(operands);
+      if (cudf::ast::detail::ast_operator_arity(op) == 2) {
+        _operators.emplace_back(op, new_operands.front(), new_operands.back());
+      } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
+        _operators.emplace_back(op, new_operands.front());
+      }
+    }
+    _equality_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    return std::reference_wrapper<ast::expression const>(_operators.back());
+  }
+
+  /**
+   * @brief Returns a list of column indices with an equality predicate in the AST expression.
+   *
+   * @return List of column indices
+   */
+  [[nodiscard]] std::vector<cudf::size_type> get_equality_col_idx() const
+  {
+    return equality_col_idx;
+  }
+
+ private:
+  std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
+    cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
+  {
+    std::vector<std::reference_wrapper<ast::expression const>> transformed_operands;
+    for (auto const& operand : operands) {
+      auto const new_operand = operand.get().accept(*this);
+      transformed_operands.push_back(new_operand);
+    }
+    return transformed_operands;
+  }
+  std::optional<std::reference_wrapper<ast::expression const>> _equality_expr;
+  std::vector<cudf::size_type> equality_col_idx;
+  size_type _num_columns;
+  std::list<ast::column_reference> _col_ref;
+  std::list<ast::operation> _operators;
+};
+
 }  // namespace
 
+std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::apply_bloom_filters(
+  host_span<std::unique_ptr<datasource> const> sources,
+  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<data_type const> output_dtypes,
+  host_span<int const> output_column_schemas,
+  std::reference_wrapper<ast::expression const> filter,
+  rmm::cuda_stream_view stream) const
+{
+  auto const num_cols = output_dtypes.size();
+  CUDF_EXPECTS(output_dtypes.size() == output_column_schemas.size(),
+               "Mismatched size between lists of output column dtypes and output column schema");
+  auto mr = cudf::get_current_device_resource_ref();
+  std::vector<std::unique_ptr<column>> cols;
+  // MH: How do I test for nested or non-comparable columns here?
+  cols.emplace_back(cudf::make_numeric_column(
+    data_type{cudf::type_id::INT32}, num_cols, rmm::device_buffer{}, 0, stream, mr));
+
+  auto mutable_col_idx = cols.back()->mutable_view();
+
+  thrust::sequence(rmm::exec_policy(stream),
+                   mutable_col_idx.begin<size_type>(),
+                   mutable_col_idx.end<size_type>(),
+                   0);
+
+  auto equality_table = cudf::table(std::move(cols));
+
+  // Converts AST to EqualityAST with reference to min, max columns in above `stats_table`.
+  equality_predicate_converter equality_expr{filter.get(), static_cast<size_type>(num_cols)};
+  auto equality_col_schemas = equality_expr.get_equality_col_idx();
+
+  // Convert column indices to column schema indices
+  std::for_each(equality_col_schemas.begin(), equality_col_schemas.end(), [&](auto& col_idx) {
+    col_idx = output_column_schemas[col_idx];
+  });
+
+  std::ignore = read_bloom_filters(sources, row_group_indices, equality_col_schemas, stream);
+
+  return std::nullopt;
+}
+
 std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index a977cfdeca7..eb30cc6955a 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -479,7 +479,9 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
                   is_row_group_required.cend(),
                   [](auto i) { return bool(i); }) or
       predicate.null_count() == predicate.size()) {
-    return std::nullopt;
+    // Call with input_row_group_indices
+    return apply_bloom_filters(
+      sources, input_row_group_indices, output_dtypes, output_column_schemas, filter, stream);
   }
   size_type is_required_idx = 0;
   for (auto const& input_row_group_index : input_row_group_indices) {
@@ -493,6 +495,10 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
     filtered_row_group_indices.push_back(std::move(filtered_row_groups));
   }
 
+  // Call with filtered_row_group_indices
+  return apply_bloom_filters(
+    sources, filtered_row_group_indices, output_dtypes, output_column_schemas, filter, stream);
+
   return {std::move(filtered_row_group_indices)};
 }
 
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index b03aa9ec296..75edfdb7f7b 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -339,6 +339,26 @@ class aggregate_reader_metadata {
     std::reference_wrapper<ast::expression const> filter,
     rmm::cuda_stream_view stream) const;
 
+  /**
+   * @brief Filters the row groups using bloom filters
+   *
+   * @param sources Dataset sources
+   * @param row_group_indices Lists of row groups to read, one per source
+   * @param output_dtypes Datatypes of of output columns
+   * @param output_column_schemas schema indices of output columns
+   * @param filter AST expression to filter row groups based on Column chunk statistics
+   * @param stream CUDA stream used for device memory operations and kernel launches
+   *
+   * @return Filtered row group indices, if any is filtered.
+   */
+  [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> apply_bloom_filters(
+    host_span<std::unique_ptr<datasource> const> sources,
+    host_span<std::vector<size_type> const> row_group_indices,
+    host_span<data_type const> output_dtypes,
+    host_span<int const> output_column_schemas,
+    std::reference_wrapper<ast::expression const> filter,
+    rmm::cuda_stream_view stream) const;
+
   /**
    * @brief Filters and reduces down to a selection of row groups
    *

From aaf355e1b2efb830ed72b2bf09957ae3a1e95e76 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 20 Nov 2024 02:45:46 +0000
Subject: [PATCH 22/82] Enable `arrow_filter_policy` and `span` types in bloom
 filter.

---
 cpp/src/io/parquet/arrow_filter_policy.cuh | 187 +++++++++++++++++++++
 cpp/src/io/parquet/bloom_filter_reader.cu  |  89 ++++++----
 2 files changed, 246 insertions(+), 30 deletions(-)
 create mode 100644 cpp/src/io/parquet/arrow_filter_policy.cuh

diff --git a/cpp/src/io/parquet/arrow_filter_policy.cuh b/cpp/src/io/parquet/arrow_filter_policy.cuh
new file mode 100644
index 00000000000..95edf68cab4
--- /dev/null
+++ b/cpp/src/io/parquet/arrow_filter_policy.cuh
@@ -0,0 +1,187 @@
+/*
+ * Copyright (c) 2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+#include <cuco/hash_functions.cuh>
+#include <cuda/functional>
+#include <cuda/std/bit>
+#include <cuda/std/limits>
+
+#include <cstdint>
+#include <nv/target>
+
+namespace cuco {
+
+/**
+ * @brief A policy that defines how Arrow Block-Split Bloom Filter generates and stores a key's
+ * fingerprint.
+ *
+ * @note: This file is a part of cuCollections. Copied here until we get a cuco bump for cudf.
+ *
+ * Reference:
+ * https://github.com/apache/arrow/blob/be1dcdb96b030639c0b56955c4c62f9d6b03f473/cpp/src/parquet/bloom_filter.cc#L219-L230
+ *
+ * Example:
+ * @code{.cpp}
+ * template <typename KeyType, std::uint32_t NUM_FILTER_BLOCKS>
+ * void bulk_insert_and_eval_arrow_policy_bloom_filter(device_vector<KeyType> const& positive_keys,
+ *                                                 device_vector<KeyType> const& negative_keys)
+ * {
+ *     using policy_type = cuco::arrow_filter_policy<key_type>;
+ *
+ *     // Warn or throw if the number of filter blocks is greater than maximum used by Arrow policy.
+ *     static_assert(NUM_FILTER_BLOCKS <= policy_type::max_filter_blocks, "NUM_FILTER_BLOCKS must be
+ *                                                                         in range: [1, 4194304]");
+ *
+ *     // Create a bloom filter with Arrow policy
+ *     cuco::bloom_filter<key_type, cuco::extent<size_t>,
+ *         cuda::thread_scope_device, policy_type> filter{NUM_FILTER_BLOCKS};
+ *
+ *     // Add positive keys to the bloom filter
+ *     filter.add(positive_keys.begin(), positive_keys.end());
+ *
+ *     auto const num_tp = positive_keys.size();
+ *     auto const num_tn = negative_keys.size();
+ *
+ *     // Vectors to store query results.
+ *     thrust::device_vector<bool> true_positive_result(num_tp, false);
+ *     thrust::device_vector<bool> true_negative_result(num_tn, false);
+ *
+ *     // Query the bloom filter for the inserted keys.
+ *     filter.contains(positive_keys.begin(), positive_keys.end(), true_positive_result.begin());
+ *
+ *     // We should see a true-positive rate of 1.
+ *     float true_positive_rate = float(thrust::count(thrust::device,
+ *          true_positive_result.begin(), true_positive_result.end(), true)) / float(num_tp);
+ *
+ *     // Query the bloom filter for the non-inserted keys.
+ *     filter.contains(negative_keys.begin(), negative_keys.end(), true_negative_result.begin());
+ *
+ *     // We may see a false-positive rate > 0 depending on the number of bits in the
+ *     // filter and the number of hashes used per key.
+ *     float false_positive_rate = float(thrust::count(thrust::device,
+ *          true_negative_result.begin(), true_negative_result.end(), true)) / float(num_tn);
+ * }
+ * @endcode
+ *
+ * @tparam Key The type of the values to generate a fingerprint for.
+ */
+template <class Key, class Hash>
+class arrow_filter_policy {
+ public:
+  using hasher             = Hash;           ///< Hash function for Arrow bloom filter policy
+  using word_type          = std::uint32_t;  ///< uint32_t for Arrow bloom filter policy
+  using hash_argument_type = typename hasher::argument_type;  ///< Hash function input type
+  using hash_result_type   = decltype(std::declval<hasher>()(
+    std::declval<hash_argument_type>()));  ///< hash function output type
+
+  static constexpr uint32_t bits_set_per_block = 8;  ///< hardcoded bits set per Arrow filter block
+  static constexpr uint32_t words_per_block    = 8;  ///< hardcoded words per Arrow filter block
+
+  static constexpr std::uint32_t bytes_per_filter_block =
+    32;  ///< Number of bytes in one Arrow filter block
+  static constexpr std::uint32_t max_arrow_filter_bytes =
+    128 * 1024 * 1024;  ///< Max bytes in Arrow bloom filter
+  static constexpr std::uint32_t max_filter_blocks =
+    (max_arrow_filter_bytes /
+     bytes_per_filter_block);  ///< Max sub-filter blocks allowed in Arrow bloom filter
+
+ private:
+  // Arrow's block-based bloom filter algorithm needs these eight odd SALT values to calculate
+  // eight indexes of bit to set, one bit in each 32-bit (uint32_t) word.
+  __device__ static constexpr cuda::std::array<std::uint32_t, 8> SALT()
+  {
+    return {0x47b6137bU,
+            0x44974d91U,
+            0x8824ad5bU,
+            0xa2b7289dU,
+            0x705495c7U,
+            0x2df1424bU,
+            0x9efc4947U,
+            0x5c6bfb31U};
+  }
+
+ public:
+  /**
+   * @brief Constructs the `arrow_filter_policy` object.
+   *
+   * @note The number of filter blocks with Arrow policy must be in the
+   * range of [1, 4194304]. If the bloom filter is constructed with a larger
+   * number of blocks, only the first 4194304 (128MB) blocks will be used.
+   *
+   * @param hash Hash function used to generate a key's fingerprint
+   */
+  __host__ __device__ constexpr arrow_filter_policy(hasher hash = {}) : hash_{hash} {}
+
+  /**
+   * @brief Generates the hash value for a given key.
+   *
+   * @param key The key to hash
+   *
+   * @return The hash value of the key
+   */
+  __device__ constexpr hash_result_type hash(hash_argument_type const& key) const
+  {
+    return hash_(key);
+  }
+
+  /**
+   * @brief Determines the filter block a key is added into.
+   *
+   * @note The number of filter blocks with Arrow policy must be in the
+   * range of [1, 4194304]. Passing a larger `num_blocks` will still
+   * upperbound the number of blocks used to the mentioned range.
+   *
+   * @tparam Extent Size type that is used to determine the number of blocks in the filter
+   *
+   * @param hash Hash value of the key
+   * @param num_blocks Number of block in the filter
+   *
+   * @return The block index for the given key's hash value
+   */
+  template <class Extent>
+  __device__ constexpr auto block_index(hash_result_type hash, Extent num_blocks) const
+  {
+    constexpr auto hash_bits = cuda::std::numeric_limits<word_type>::digits;
+    // TODO: assert if num_blocks > max_filter_blocks
+    auto const max_blocks = cuda::std::min<Extent>(num_blocks, max_filter_blocks);
+    // Make sure we are only contained withing the `max_filter_blocks` blocks
+    return static_cast<word_type>(((hash >> hash_bits) * max_blocks) >> hash_bits) % max_blocks;
+  }
+
+  /**
+   * @brief Determines the fingerprint pattern for a word/segment within the filter block for a
+   * given key's hash value.
+   *
+   * @param hash Hash value of the key
+   * @param word_index Target word/segment within the filter block
+   *
+   * @return The bit pattern for the word/segment in the filter block
+   */
+  __device__ constexpr word_type word_pattern(hash_result_type hash, std::uint32_t word_index) const
+  {
+    // SALT array to calculate bit indexes for the current word
+    auto constexpr salt = SALT();
+    word_type const key = static_cast<word_type>(hash);
+    return word_type{1} << ((key * salt[word_index]) >> 27);
+  }
+
+ private:
+  hasher hash_;
+};
+
+}  // namespace cuco
\ No newline at end of file
diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 89f448de05f..5178fbba3c1 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -14,6 +14,7 @@
  * limitations under the License.
  */
 
+#include "arrow_filter_policy.cuh"
 #include "compact_protocol_reader.hpp"
 #include "io/parquet/parquet.hpp"
 #include "reader_impl_helpers.hpp"
@@ -36,6 +37,7 @@
 #include <cuco/bloom_filter_policy.cuh>
 #include <cuco/bloom_filter_ref.cuh>
 #include <cuco/hash_functions.cuh>
+#include <cuda/std/span>
 #include <thrust/for_each.h>
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/sequence.h>
@@ -48,6 +50,61 @@
 namespace cudf::io::parquet::detail {
 
 namespace {
+
+/**
+ * @brief Temporary function that tests for key `third-037493` in bloom filters of column `c2` in
+ * test Parquet file.
+ *
+ * @param buffer Device buffer containing bloom filter bitset
+ * @param chunk Current row group index
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ *
+ */
+void check_arbitrary_string_key(rmm::device_buffer const& buffer,
+                                size_t chunk,
+                                rmm::cuda_stream_view stream)
+{
+  using word_type   = cuda::std::uint32_t;
+  using key_type    = cuda::std::span<cuda::std::byte>;
+  using policy_type = cuco::arrow_filter_policy<key_type, cuco::xxhash_64<key_type>>;
+
+  thrust::for_each(
+    rmm::exec_policy_nosync(stream),
+    thrust::make_counting_iterator(0),
+    thrust::make_counting_iterator(1),
+    [bitset     = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data())),
+     num_blocks = static_cast<cuda::std::size_t>(buffer.size()) / sizeof(uint32_t),
+     chunk      = chunk,
+     stream     = stream] __device__(auto idx) {
+      // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
+      cuco::bloom_filter_ref<key_type,
+                             cuco::extent<std::size_t>,
+                             cuco::thread_scope_device,
+                             policy_type>
+        filter{
+          bitset,
+          num_blocks,
+          {},  // scope
+          {0}  // policy
+        };
+
+      // literal to search
+      cudf::string_view literal("third-037493", sizeof("third-037493"));
+      // convert to a cuda::std::span key to search
+      cuda::std::span<cuda::std::byte> const key(
+        const_cast<cuda::std::byte*>(reinterpret_cast<cuda::std::byte const*>(literal.data())),
+        static_cast<cuda::std::size_t>(literal.length()));
+      // Search in the filter
+      if (filter.contains(key)) {
+        printf("YES: Filter chunk: %lu contains key: third-037493\n", chunk);
+      } else {
+        printf("NO: Filter chunk: %lu does not contain key: third-037493\n", chunk);
+      }
+    });
+
+  stream.synchronize_no_throw();
+}
+
 /**
  * @brief Asynchronously reads bloom filters to device.
  *
@@ -119,36 +176,8 @@ std::future<void> read_bloom_filters_async(
           bloom_filter_data[chunk] =
             rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
 
-          /* MH: Remove this
-          using word_type = uint32_t;
-
-          thrust::for_each(rmm::exec_policy(stream),
-                           thrust::make_counting_iterator(0),
-                           thrust::make_counting_iterator(1),
-                           [words = reinterpret_cast<word_type*>(bloom_filter_data[chunk].data()),
-                            num_blocks = bloom_filter_data[chunk].size() / sizeof(uint32_t),
-                            chunk      = chunk,
-                            stream     = stream] __device__(auto idx) {
-                             using key_type = cuda::std::string;
-                             using policy_type =
-                               cuco::bloom_filter_policy<cuco::xxhash_64<key_type>, std::uint32_t,
-          8>;
-                             // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
-                             cuco::bloom_filter_ref<key_type,
-                                                    cuco::extent<std::size_t>,
-                                                    cuco::thread_scope_device,
-                                                    policy_type>
-                               filter{words, size_t{num_blocks}, {}, {8}};
-                             // cuda::std::string key{"third-136666"};
-                             // filter.add("third-136666");
-
-                             cuco::xxhash_64<key_type> hasher{};
-                             cuda::std::array<char, 13> val{"third-136666"};
-                             auto hash =
-          hasher.compute_hash(reinterpret_cast<std::byte*>(val.data()), val.size()); if
-          (filter.contains(hash)) { printf("Filter chunk: %lu contains key: third-136666\n", chunk);
-                             }
-                           });*/
+          // MH: TODO: Temporary test. Remove me!!
+          check_arbitrary_string_key(bloom_filter_data[chunk], chunk, stream);
         }
         // Read the bitset from datasource.
         else {

From e92324ebe0eaa1cb0a1a214f713ffe4aba36743f Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 21 Nov 2024 08:41:10 +0000
Subject: [PATCH 23/82] Successfully search bloom filter

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 148 ++++++++++++++++++----
 1 file changed, 124 insertions(+), 24 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 5178fbba3c1..3c0c906a448 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -22,22 +22,18 @@
 #include <cudf/ast/detail/expression_transformer.hpp>
 #include <cudf/ast/detail/operators.hpp>
 #include <cudf/ast/expressions.hpp>
-#include <cudf/column/column_factories.hpp>
 #include <cudf/detail/cuco_helpers.hpp>
-#include <cudf/detail/iterator.cuh>
 #include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
-#include <cudf/utilities/error.hpp>
+#include <cudf/hashing/detail/xxhash_64.cuh>
 
 #include <rmm/cuda_stream_view.hpp>
 #include <rmm/device_buffer.hpp>
 #include <rmm/device_vector.hpp>
 #include <rmm/exec_policy.hpp>
 
-#include <cuco/bloom_filter_policy.cuh>
+#include <cuco/bloom_filter.cuh>
 #include <cuco/bloom_filter_ref.cuh>
-#include <cuco/hash_functions.cuh>
-#include <cuda/std/span>
 #include <thrust/for_each.h>
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/sequence.h>
@@ -46,11 +42,115 @@
 #include <iterator>
 #include <numeric>
 #include <optional>
+#include <random>
 
 namespace cudf::io::parquet::detail {
 
 namespace {
 
+std::pair<std::vector<char>, std::vector<size_t>> generate_chars_and_offsets(size_t num_keys)
+{
+  static std::vector<std::string> const strings{"first",
+                                                "second",
+                                                "third",
+                                                "fourth",
+                                                "fifth",
+                                                "sixth",
+                                                "seventh",
+                                                "eighth",
+                                                "ninth",
+                                                "tenth",
+                                                "eleventh",
+                                                "twelfth",
+                                                "thirteenth",
+                                                "fourteenth",
+                                                "fifteenth",
+                                                "sixteenth",
+                                                "seventeenth",
+                                                "eighteenth"};
+
+  auto constexpr seed = 0xf00d;
+  /*static*/ std::mt19937 engine{seed};
+  /*static*/ std::uniform_int_distribution dist{};
+
+  std::vector<size_t> offsets(num_keys + 1);
+  std::vector<char> chars;
+  chars.reserve(12 * num_keys);  // 12 is the length of "seventeenth", the largest string
+  size_t offset = 0;
+  offsets[0]    = size_t{0};
+  std::generate_n(offsets.begin() + 1, num_keys, [&]() {
+    auto const& string  = strings[dist(engine) % strings.size()];
+    auto const char_ptr = const_cast<char*>(string.data());
+    chars.insert(chars.end(), char_ptr, char_ptr + string.length());
+    offset += string.length();
+    return offset;
+  });
+  return {std::move(chars), std::move(offsets)};
+}
+
+void validate_filter_bitwise(rmm::cuda_stream_view stream)
+{
+  std::size_t constexpr num_filter_blocks = 4;
+  std::size_t constexpr num_keys          = 50;
+
+  // Generate strings data
+  auto const [h_chars, h_offsets] = generate_chars_and_offsets(num_keys);
+  auto const mr                   = cudf::get_current_device_resource_ref();
+  auto d_chars                    = cudf::detail::make_device_uvector_async(h_chars, stream, mr);
+  auto d_offsets                  = cudf::detail::make_device_uvector_async(h_offsets, stream, mr);
+
+  rmm::device_uvector<cudf::string_view> d_keys(num_keys, stream);
+  thrust::transform(rmm::exec_policy_nosync(stream),
+                    thrust::make_counting_iterator<size_t>(0),
+                    thrust::make_counting_iterator<size_t>(num_keys),
+                    d_keys.begin(),
+                    [chars   = thrust::raw_pointer_cast(d_chars.data()),
+                     offsets = thrust::raw_pointer_cast(d_offsets.data())] __device__(auto idx) {
+                      return cudf::string_view{
+                        chars + offsets[idx],
+                        static_cast<cudf::size_type>(offsets[idx + 1] - offsets[idx])};
+                    });
+
+  using key_type    = cudf::string_view;
+  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
+  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+  using filter_type = cuco::bloom_filter<key_type,
+                                         cuco::extent<size_t>,
+                                         cuda::thread_scope_device,
+                                         policy_type,
+                                         cudf::detail::cuco_allocator<char>>;
+  // Spawn a bloom filter
+  filter_type filter{
+    num_filter_blocks,
+    cuco::thread_scope_device,
+    {hasher_type{0}},
+    cudf::detail::cuco_allocator<char>{rmm::mr::polymorphic_allocator<char>{}, stream},
+    stream};
+
+  // Add strings to the bloom filter
+  filter.add(d_keys.begin(), d_keys.end(), stream);
+
+  using word_type = filter_type::word_type;
+
+  // Number of words in the filter
+  size_t const num_words = filter.block_extent() * filter.words_per_block;
+
+  // Get the filter bitset words
+  cudf::device_span<word_type const> filter_bitset(filter.data(), num_words);
+  // Expected filter bitset words
+  rmm::device_vector<word_type> const expected_bitset{
+    4194306,    4194305,  2359296,   1073774592, 524544,     1024,       268443648,  8519680,
+    2147500040, 8421380,  269500416, 4202624,    8396802,    100665344,  2147747840, 5243136,
+    131146,     655364,   285345792, 134222340,  545390596,  2281717768, 51201,      41943553,
+    1619656708, 67441680, 8462730,   361220,     2216738864, 587333888,  4219272,    873463873};
+
+  CUDF_EXPECTS(thrust::equal(rmm::exec_policy(stream),
+                             expected_bitset.cbegin(),
+                             expected_bitset.cend(),
+                             filter_bitset.begin()),
+               "Bloom filter bitset mismatched");
+}
+
 /**
  * @brief Temporary function that tests for key `third-037493` in bloom filters of column `c2` in
  * test Parquet file.
@@ -64,16 +164,21 @@ void check_arbitrary_string_key(rmm::device_buffer const& buffer,
                                 size_t chunk,
                                 rmm::cuda_stream_view stream)
 {
-  using word_type   = cuda::std::uint32_t;
-  using key_type    = cuda::std::span<cuda::std::byte>;
-  using policy_type = cuco::arrow_filter_policy<key_type, cuco::xxhash_64<key_type>>;
+  using key_type    = cudf::string_view;
+  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
+  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+  using word_type   = policy_type::word_type;
+
+  auto constexpr word_size       = sizeof(word_type);
+  auto constexpr words_per_block = policy_type::words_per_block;
+  auto const num_filter_blocks   = buffer.size() / (word_size * words_per_block);
 
   thrust::for_each(
-    rmm::exec_policy_nosync(stream),
+    rmm::exec_policy(stream),
     thrust::make_counting_iterator(0),
     thrust::make_counting_iterator(1),
     [bitset     = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data())),
-     num_blocks = static_cast<cuda::std::size_t>(buffer.size()) / sizeof(uint32_t),
+     num_blocks = num_filter_blocks,
      chunk      = chunk,
      stream     = stream] __device__(auto idx) {
       // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
@@ -81,19 +186,13 @@ void check_arbitrary_string_key(rmm::device_buffer const& buffer,
                              cuco::extent<std::size_t>,
                              cuco::thread_scope_device,
                              policy_type>
-        filter{
-          bitset,
-          num_blocks,
-          {},  // scope
-          {0}  // policy
-        };
+        filter{bitset,
+               num_blocks,
+               {},  // scope
+               {hasher_type{0}}};
 
       // literal to search
-      cudf::string_view literal("third-037493", sizeof("third-037493"));
-      // convert to a cuda::std::span key to search
-      cuda::std::span<cuda::std::byte> const key(
-        const_cast<cuda::std::byte*>(reinterpret_cast<cuda::std::byte const*>(literal.data())),
-        static_cast<cuda::std::size_t>(literal.length()));
+      cudf::string_view key("third-037493", 12);
       // Search in the filter
       if (filter.contains(key)) {
         printf("YES: Filter chunk: %lu contains key: third-037493\n", chunk);
@@ -101,8 +200,6 @@ void check_arbitrary_string_key(rmm::device_buffer const& buffer,
         printf("NO: Filter chunk: %lu does not contain key: third-037493\n", chunk);
       }
     });
-
-  stream.synchronize_no_throw();
 }
 
 /**
@@ -206,6 +303,9 @@ std::future<void> read_bloom_filters_async(
     }
   };
 
+  // MH: Remove me. Bitwise validation for bloom filter
+  validate_filter_bitwise(stream);
+
   return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
 }
 

From 0b1719d61d0838ecc57cb3f6c7605d656c5491b6 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 21 Nov 2024 19:03:22 +0000
Subject: [PATCH 24/82] style fix

---
 cpp/src/io/parquet/arrow_filter_policy.cuh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/arrow_filter_policy.cuh b/cpp/src/io/parquet/arrow_filter_policy.cuh
index 95edf68cab4..dfb6745bed8 100644
--- a/cpp/src/io/parquet/arrow_filter_policy.cuh
+++ b/cpp/src/io/parquet/arrow_filter_policy.cuh
@@ -184,4 +184,4 @@ class arrow_filter_policy {
   hasher hash_;
 };
 
-}  // namespace cuco
\ No newline at end of file
+}  // namespace cuco

From ef3a26212e38759f2aae8b1dbddb07576455d186 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Fri, 22 Nov 2024 02:35:00 +0000
Subject: [PATCH 25/82] Code cleanup

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 80 +++++++++++++----------
 1 file changed, 46 insertions(+), 34 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 3c0c906a448..6eed5c5dd21 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -34,8 +34,8 @@
 
 #include <cuco/bloom_filter.cuh>
 #include <cuco/bloom_filter_ref.cuh>
-#include <thrust/for_each.h>
 #include <thrust/iterator/counting_iterator.h>
+#include <thrust/logical.h>
 #include <thrust/sequence.h>
 
 #include <future>
@@ -155,51 +155,61 @@ void validate_filter_bitwise(rmm::cuda_stream_view stream)
  * @brief Temporary function that tests for key `third-037493` in bloom filters of column `c2` in
  * test Parquet file.
  *
+ * @tparam Key Type of the key to query bloom filter.
+ *
  * @param buffer Device buffer containing bloom filter bitset
  * @param chunk Current row group index
  * @param stream CUDA stream used for device memory operations and kernel launches
  *
  */
-void check_arbitrary_string_key(rmm::device_buffer const& buffer,
-                                size_t chunk,
-                                rmm::cuda_stream_view stream)
+template <typename Key = cudf::string_view>
+[[nodiscard]] bool check_arbitrary_string_key(rmm::device_buffer const& buffer,
+                                              Key const& literal,
+                                              size_t chunk_idx,
+                                              rmm::cuda_stream_view stream)
 {
-  using key_type    = cudf::string_view;
+  using key_type    = Key;
   using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
   using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
-  using word_type   = policy_type::word_type;
+  using word_type   = typename policy_type::word_type;
 
+  // Filter properties
   auto constexpr word_size       = sizeof(word_type);
   auto constexpr words_per_block = policy_type::words_per_block;
   auto const num_filter_blocks   = buffer.size() / (word_size * words_per_block);
 
-  thrust::for_each(
-    rmm::exec_policy(stream),
-    thrust::make_counting_iterator(0),
-    thrust::make_counting_iterator(1),
-    [bitset     = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data())),
-     num_blocks = num_filter_blocks,
-     chunk      = chunk,
-     stream     = stream] __device__(auto idx) {
-      // using arrow_policy_type = cuco::arrow_filter_policy<key_type>;
-      cuco::bloom_filter_ref<key_type,
-                             cuco::extent<std::size_t>,
-                             cuco::thread_scope_device,
-                             policy_type>
-        filter{bitset,
-               num_blocks,
-               {},  // scope
-               {hasher_type{0}}};
-
-      // literal to search
-      cudf::string_view key("third-037493", 12);
-      // Search in the filter
-      if (filter.contains(key)) {
-        printf("YES: Filter chunk: %lu contains key: third-037493\n", chunk);
-      } else {
-        printf("NO: Filter chunk: %lu does not contain key: third-037493\n", chunk);
-      }
-    });
+  // Bitset ptr must be a non-const to be used in bloom_filter_ref.
+  auto bitset = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data()));
+
+  // Create a bloom filter view
+  cuco::
+    bloom_filter_ref<key_type, cuco::extent<std::size_t>, cuco::thread_scope_device, policy_type>
+      filter{bitset,
+             num_filter_blocks,
+             {},  // scope
+             {hasher_type{0}}};
+
+  // Copy over the key (literal) to device
+  rmm::device_buffer d_key{literal.data(), static_cast<size_t>(literal.size_bytes()), stream};
+
+  // Query literal in bloom filter.
+  bool const is_literal_found =
+    thrust::count_if(rmm::exec_policy(stream),
+                     thrust::make_counting_iterator(0),
+                     thrust::make_counting_iterator(1),
+                     [filter   = filter,
+                      key_ptr  = reinterpret_cast<char*>(d_key.data()),
+                      key_size = static_cast<cudf::size_type>(d_key.size())] __device__(auto idx) {
+                       auto const d_key = cudf::string_view{key_ptr, key_size};
+                       return filter.contains(d_key);
+                     });
+
+  // MH: Temporary
+  auto const found_string = (is_literal_found) ? "YES" : "NO";
+  std::cout << "Literal: third-037493 found in chunk " << chunk_idx << ": " << found_string
+            << std::endl;
+
+  return is_literal_found;
 }
 
 /**
@@ -274,7 +284,9 @@ std::future<void> read_bloom_filters_async(
             rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
 
           // MH: TODO: Temporary test. Remove me!!
-          check_arbitrary_string_key(bloom_filter_data[chunk], chunk, stream);
+          cudf::string_view literal{"third-037493", 12};
+          std::ignore =
+            check_arbitrary_string_key(bloom_filter_data[chunk], literal, chunk, stream);
         }
         // Read the bitset from datasource.
         else {

From 051be2d6caad8b4ad78b0a9d5e0f2880f7b37198 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Mon, 25 Nov 2024 21:30:54 +0000
Subject: [PATCH 26/82] add tests

---
 cpp/tests/CMakeLists.txt               |  1 +
 cpp/tests/hashing/bloom_filter_test.cu | 95 ++++++++++++++++++++++++++
 2 files changed, 96 insertions(+)
 create mode 100644 cpp/tests/hashing/bloom_filter_test.cu

diff --git a/cpp/tests/CMakeLists.txt b/cpp/tests/CMakeLists.txt
index 8928d27a871..94a5063d150 100644
--- a/cpp/tests/CMakeLists.txt
+++ b/cpp/tests/CMakeLists.txt
@@ -182,6 +182,7 @@ ConfigureTest(DATETIME_OPS_TEST datetime/datetime_ops_test.cpp)
 # * hashing tests ---------------------------------------------------------------------------------
 ConfigureTest(
   HASHING_TEST
+  hashing/bloom_filter_test.cu
   hashing/md5_test.cpp
   hashing/murmurhash3_x86_32_test.cpp
   hashing/murmurhash3_x64_128_test.cpp
diff --git a/cpp/tests/hashing/bloom_filter_test.cu b/cpp/tests/hashing/bloom_filter_test.cu
new file mode 100644
index 00000000000..e0e98dd84a0
--- /dev/null
+++ b/cpp/tests/hashing/bloom_filter_test.cu
@@ -0,0 +1,95 @@
+/*
+ * Copyright (c) 2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*
+#include <cudf_test/base_fixture.hpp>
+#include <cudf_test/column_utilities.hpp>
+#include <cudf_test/column_wrapper.hpp>
+#include <cudf_test/iterator_utilities.hpp>
+
+#include <cudf/detail/cuco_helpers.hpp>
+#include <cudf/hashing/detail/xxhash_64.cuh>
+#include <cudf/utilities/default_stream.hpp>
+
+#include <cuco/bloom_filter.cuh>
+
+using StringType = cudf::string_view;
+
+template <typename T>
+class BloomFilter_TestTyped : public cudf::test::BaseFixture {};
+
+TYPED_TEST_SUITE(BloomFilter_TestTyped, StringType);
+
+TYPED_TEST(BloomFilter_TestTyped, TestStrings)
+{
+  using key_type    = StringType;
+  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
+  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+
+  std::size_t constexpr num_filter_blocks = 4;
+  std::size_t constexpr num_keys          = 50;
+  auto stream                             = cudf::get_default_stream();
+
+  // strings data
+  auto data = cudf::test::strings_column_wrapper(
+    {"seventh",    "fifteenth",   "second",      "tenth",      "fifth",       "first",
+     "seventh",    "tenth",       "ninth",       "ninth",      "seventeenth", "eighteenth",
+     "thirteenth", "fifth",       "fourth",      "twelfth",    "second",      "second",
+     "fourth",     "seventh",     "seventh",     "tenth",      "thirteenth",  "seventeenth",
+     "fifth",      "seventeenth", "eighth",      "fourth",     "second",      "eighteenth",
+     "fifteenth",  "second",      "seventeenth", "thirteenth", "eighteenth",  "fifth",
+     "seventh",    "tenth",       "fourteenth",  "first",      "fifth",       "fifth",
+     "tenth",      "thirteenth",  "fourteenth",  "third",      "third",       "sixth",
+     "first",      "third"});
+  auto d_column = cudf::column_device_view::create(data);
+
+  // Spawn a bloom filter
+  cuco::bloom_filter<key_type,
+                     cuco::extent<size_t>,
+                     cuda::thread_scope_device,
+                     policy_type,
+                     cudf::detail::cuco_allocator<char>>
+    filter{num_filter_blocks,
+           cuco::thread_scope_device,
+           {hasher_type{0}},
+           cudf::detail::cuco_allocator<char>{rmm::mr::polymorphic_allocator<char>{}, stream},
+           stream};
+
+  // Add strings to the bloom filter
+  auto col = table.column(0);
+  filter.add(d_column->begin<key_type>(), d_column->end<key_type>(), stream);
+
+  // Number of words in the filter
+  cudf::size_type const num_words = filter.block_extent() * filter.words_per_block;
+
+  auto const output = cudf::column_view{
+    cudf::data_type{cudf::type_id::UINT32}, num_words, filter.data(), nullptr, 0, 0, {}};
+
+  using word_type = filter_type::word_type;
+
+  // Expected filter bitset words computed using Arrow implementation here:
+  // https://godbolt.org/z/oKfqcPWbY
+  auto expected = cudf::test::fixed_width_column_wrapper<word_type>(
+    {4194306,    4194305,  2359296,   1073774592, 524544,     1024,       268443648,  8519680,
+     2147500040, 8421380,  269500416, 4202624,    8396802,    100665344,  2147747840, 5243136,
+     131146,     655364,   285345792, 134222340,  545390596,  2281717768, 51201,      41943553,
+     1619656708, 67441680, 8462730,   361220,     2216738864, 587333888,  4219272,    873463873});
+  auto d_expected = cudf::column_device_view::create(expected);
+
+  // Check
+  CUDF_TEST_EXPECT_COLUMNS_EQUAL(output, d_expected);
+}
+*/
\ No newline at end of file

From fb55c3f0f689f7ba9084506acb060072c320be56 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 26 Nov 2024 05:00:27 +0000
Subject: [PATCH 27/82] Major cleanups

---
 cpp/CMakeLists.txt                         |   1 +
 cpp/src/io/parquet/bloom_filter_reader.cu  | 739 ++++++++++++---------
 cpp/src/io/parquet/predicate_pushdown.cpp  |   9 +-
 cpp/src/io/parquet/reader_impl_helpers.hpp |  38 +-
 4 files changed, 442 insertions(+), 345 deletions(-)

diff --git a/cpp/CMakeLists.txt b/cpp/CMakeLists.txt
index e4fa3b28383..cc14489654c 100644
--- a/cpp/CMakeLists.txt
+++ b/cpp/CMakeLists.txt
@@ -502,6 +502,7 @@ add_library(
   src/datetime/timezone.cpp
   src/io/orc/writer_impl.cu
   src/io/parquet/arrow_schema_writer.cpp
+  src/io/parquet/bloom_filter_reader.cu
   src/io/parquet/compact_protocol_reader.cpp
   src/io/parquet/compact_protocol_writer.cpp
   src/io/parquet/decode_preprocess.cu
diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 6eed5c5dd21..ecf59238a49 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -17,12 +17,14 @@
 #include "arrow_filter_policy.cuh"
 #include "compact_protocol_reader.hpp"
 #include "io/parquet/parquet.hpp"
+#include "io/parquet/parquet_gpu.hpp"
 #include "reader_impl_helpers.hpp"
 
 #include <cudf/ast/detail/expression_transformer.hpp>
 #include <cudf/ast/detail/operators.hpp>
 #include <cudf/ast/expressions.hpp>
 #include <cudf/detail/cuco_helpers.hpp>
+#include <cudf/detail/iterator.cuh>
 #include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
 #include <cudf/hashing/detail/xxhash_64.cuh>
@@ -32,7 +34,6 @@
 #include <rmm/device_vector.hpp>
 #include <rmm/exec_policy.hpp>
 
-#include <cuco/bloom_filter.cuh>
 #include <cuco/bloom_filter_ref.cuh>
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/logical.h>
@@ -45,291 +46,95 @@
 #include <random>
 
 namespace cudf::io::parquet::detail {
-
 namespace {
 
-std::pair<std::vector<char>, std::vector<size_t>> generate_chars_and_offsets(size_t num_keys)
-{
-  static std::vector<std::string> const strings{"first",
-                                                "second",
-                                                "third",
-                                                "fourth",
-                                                "fifth",
-                                                "sixth",
-                                                "seventh",
-                                                "eighth",
-                                                "ninth",
-                                                "tenth",
-                                                "eleventh",
-                                                "twelfth",
-                                                "thirteenth",
-                                                "fourteenth",
-                                                "fifteenth",
-                                                "sixteenth",
-                                                "seventeenth",
-                                                "eighteenth"};
-
-  auto constexpr seed = 0xf00d;
-  /*static*/ std::mt19937 engine{seed};
-  /*static*/ std::uniform_int_distribution dist{};
-
-  std::vector<size_t> offsets(num_keys + 1);
-  std::vector<char> chars;
-  chars.reserve(12 * num_keys);  // 12 is the length of "seventeenth", the largest string
-  size_t offset = 0;
-  offsets[0]    = size_t{0};
-  std::generate_n(offsets.begin() + 1, num_keys, [&]() {
-    auto const& string  = strings[dist(engine) % strings.size()];
-    auto const char_ptr = const_cast<char*>(string.data());
-    chars.insert(chars.end(), char_ptr, char_ptr + string.length());
-    offset += string.length();
-    return offset;
-  });
-  return {std::move(chars), std::move(offsets)};
-}
-
-void validate_filter_bitwise(rmm::cuda_stream_view stream)
-{
-  std::size_t constexpr num_filter_blocks = 4;
-  std::size_t constexpr num_keys          = 50;
-
-  // Generate strings data
-  auto const [h_chars, h_offsets] = generate_chars_and_offsets(num_keys);
-  auto const mr                   = cudf::get_current_device_resource_ref();
-  auto d_chars                    = cudf::detail::make_device_uvector_async(h_chars, stream, mr);
-  auto d_offsets                  = cudf::detail::make_device_uvector_async(h_offsets, stream, mr);
-
-  rmm::device_uvector<cudf::string_view> d_keys(num_keys, stream);
-  thrust::transform(rmm::exec_policy_nosync(stream),
-                    thrust::make_counting_iterator<size_t>(0),
-                    thrust::make_counting_iterator<size_t>(num_keys),
-                    d_keys.begin(),
-                    [chars   = thrust::raw_pointer_cast(d_chars.data()),
-                     offsets = thrust::raw_pointer_cast(d_offsets.data())] __device__(auto idx) {
-                      return cudf::string_view{
-                        chars + offsets[idx],
-                        static_cast<cudf::size_type>(offsets[idx + 1] - offsets[idx])};
-                    });
-
-  using key_type    = cudf::string_view;
-  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
-  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
-  using filter_type = cuco::bloom_filter<key_type,
-                                         cuco::extent<size_t>,
-                                         cuda::thread_scope_device,
-                                         policy_type,
-                                         cudf::detail::cuco_allocator<char>>;
-  // Spawn a bloom filter
-  filter_type filter{
-    num_filter_blocks,
-    cuco::thread_scope_device,
-    {hasher_type{0}},
-    cudf::detail::cuco_allocator<char>{rmm::mr::polymorphic_allocator<char>{}, stream},
-    stream};
-
-  // Add strings to the bloom filter
-  filter.add(d_keys.begin(), d_keys.end(), stream);
-
-  using word_type = filter_type::word_type;
-
-  // Number of words in the filter
-  size_t const num_words = filter.block_extent() * filter.words_per_block;
-
-  // Get the filter bitset words
-  cudf::device_span<word_type const> filter_bitset(filter.data(), num_words);
-  // Expected filter bitset words
-  rmm::device_vector<word_type> const expected_bitset{
-    4194306,    4194305,  2359296,   1073774592, 524544,     1024,       268443648,  8519680,
-    2147500040, 8421380,  269500416, 4202624,    8396802,    100665344,  2147747840, 5243136,
-    131146,     655364,   285345792, 134222340,  545390596,  2281717768, 51201,      41943553,
-    1619656708, 67441680, 8462730,   361220,     2216738864, 587333888,  4219272,    873463873};
-
-  CUDF_EXPECTS(thrust::equal(rmm::exec_policy(stream),
-                             expected_bitset.cbegin(),
-                             expected_bitset.cend(),
-                             filter_bitset.begin()),
-               "Bloom filter bitset mismatched");
-}
-
 /**
- * @brief Temporary function that tests for key `third-037493` in bloom filters of column `c2` in
- * test Parquet file.
- *
- * @tparam Key Type of the key to query bloom filter.
- *
- * @param buffer Device buffer containing bloom filter bitset
- * @param chunk Current row group index
- * @param stream CUDA stream used for device memory operations and kernel launches
- *
- */
-template <typename Key = cudf::string_view>
-[[nodiscard]] bool check_arbitrary_string_key(rmm::device_buffer const& buffer,
-                                              Key const& literal,
-                                              size_t chunk_idx,
-                                              rmm::cuda_stream_view stream)
-{
-  using key_type    = Key;
-  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
-  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
-  using word_type   = typename policy_type::word_type;
-
-  // Filter properties
-  auto constexpr word_size       = sizeof(word_type);
-  auto constexpr words_per_block = policy_type::words_per_block;
-  auto const num_filter_blocks   = buffer.size() / (word_size * words_per_block);
-
-  // Bitset ptr must be a non-const to be used in bloom_filter_ref.
-  auto bitset = const_cast<word_type*>(reinterpret_cast<word_type const*>(buffer.data()));
-
-  // Create a bloom filter view
-  cuco::
-    bloom_filter_ref<key_type, cuco::extent<std::size_t>, cuco::thread_scope_device, policy_type>
-      filter{bitset,
-             num_filter_blocks,
-             {},  // scope
-             {hasher_type{0}}};
-
-  // Copy over the key (literal) to device
-  rmm::device_buffer d_key{literal.data(), static_cast<size_t>(literal.size_bytes()), stream};
-
-  // Query literal in bloom filter.
-  bool const is_literal_found =
-    thrust::count_if(rmm::exec_policy(stream),
-                     thrust::make_counting_iterator(0),
-                     thrust::make_counting_iterator(1),
-                     [filter   = filter,
-                      key_ptr  = reinterpret_cast<char*>(d_key.data()),
-                      key_size = static_cast<cudf::size_type>(d_key.size())] __device__(auto idx) {
-                       auto const d_key = cudf::string_view{key_ptr, key_size};
-                       return filter.contains(d_key);
-                     });
-
-  // MH: Temporary
-  auto const found_string = (is_literal_found) ? "YES" : "NO";
-  std::cout << "Literal: third-037493 found in chunk " << chunk_idx << ": " << found_string
-            << std::endl;
-
-  return is_literal_found;
-}
-
-/**
- * @brief Asynchronously reads bloom filters to device.
- *
- * @param sources Dataset sources
- * @param num_chunks Number of total column chunks to read
- * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
- * @param bloom_filter_offsets Bloom filter offsets for all chunks
- * @param bloom_filter_sizes Bloom filter sizes for all chunks
- * @param chunk_source_map Association between each column chunk and its source
- * @param stream CUDA stream used for device memory operations and kernel launches
+ * @brief Converts bloom filter query results for column chunks to a device column.
  *
- * @return A future object for reading synchronization
  */
-std::future<void> read_bloom_filters_async(
-  host_span<std::unique_ptr<datasource> const> sources,
-  size_t num_chunks,
-  cudf::host_span<rmm::device_buffer> bloom_filter_data,
-  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
-  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
-  std::vector<size_type> const& chunk_source_map,
-  rmm::cuda_stream_view stream)
-{
-  // Read tasks for bloom filter data
-  std::vector<std::future<size_t>> read_tasks;
-
-  // Read bloom filters for all column chunks
-  std::for_each(
-    thrust::make_counting_iterator<size_t>(0),
-    thrust::make_counting_iterator<size_t>(num_chunks),
-    [&](auto const chunk) {
-      // Read bloom filter if present
-      if (bloom_filter_offsets[chunk].has_value()) {
-        auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
-        // If Bloom filter size (header + bitset) is available, just read the entire thing.
-        // Else just read 256 bytes which will contain the entire header and may contain the
-        // entire bitset as well.
-        auto constexpr bloom_filter_header_size_guess = 256;
-        auto const initial_read_size =
-          bloom_filter_sizes[chunk].value_or(bloom_filter_header_size_guess);
-
-        // Read an initial buffer from source
-        auto& source = sources[chunk_source_map[chunk]];
-        auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
-
-        // Deserialize the Bloom filter header from the buffer.
-        BloomFilterHeader header;
-        CompactProtocolReader cp{buffer->data(), buffer->size()};
-        cp.read(&header);
-
-        // Test if header is valid.
-        auto const is_header_valid =
-          (header.num_bytes % 32) == 0 and
-          header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
-          header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
-          header.hash.hash == BloomFilterHash::Hash::XXHASH;
-
-        // Do not read if the bloom filter is invalid
-        if (not is_header_valid) {
-          CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
-          return;
-        }
-
-        // Bloom filter header size
-        auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
-        auto const bitset_size              = header.num_bytes;
-
-        // Check if we already read in the filter bitset in the initial read.
-        if (initial_read_size >= bloom_filter_header_size + bitset_size) {
-          bloom_filter_data[chunk] =
-            rmm::device_buffer(buffer->data() + bloom_filter_header_size, bitset_size, stream);
-
-          // MH: TODO: Temporary test. Remove me!!
-          cudf::string_view literal{"third-037493", 12};
-          std::ignore =
-            check_arbitrary_string_key(bloom_filter_data[chunk], literal, chunk, stream);
-        }
-        // Read the bitset from datasource.
-        else {
-          auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
-          // Directly read to device if preferred
-          if (source->is_device_read_preferred(bitset_size)) {
-            bloom_filter_data[chunk] = rmm::device_buffer(bitset_size, stream);
-            auto future_read_size =
-              source->device_read_async(bitset_offset,
-                                        bitset_size,
-                                        static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
-                                        stream);
-
-            read_tasks.emplace_back(std::move(future_read_size));
-          } else {
-            buffer                   = source->host_read(bitset_offset, bitset_size);
-            bloom_filter_data[chunk] = rmm::device_buffer(buffer->data(), buffer->size(), stream);
-          }
-        }
-      }
-    });
-
-  auto sync_fn = [](decltype(read_tasks) read_tasks) {
-    for (auto& task : read_tasks) {
-      task.wait();
+struct bloom_filter_caster {
+  size_t num_row_groups;
+  size_t num_equality_columns;
+
+  // Creates device columns from column statistics (min, max)
+  template <typename T>
+  std::unique_ptr<cudf::column> operator()(cudf::device_span<void* const> buffer_ptrs,
+                                           cudf::device_span<size_t const> buffer_sizes,
+                                           cudf::size_type equality_col_idx,
+                                           cudf::data_type dtype,
+                                           ast::literal* const& literal,
+                                           rmm::cuda_stream_view stream,
+                                           rmm::device_async_resource_ref mr) const
+  {
+    // List, Struct, Dictionary types are not supported
+    if constexpr (cudf::is_compound<T>() && !std::is_same_v<T, string_view>) {
+      CUDF_FAIL("Compound types don't support equality predicate");
+    } else {
+      CUDF_EXPECTS(dtype.id() == literal->get_data_type().id(), "Mismatched data_types");
+
+      using key_type    = T;
+      using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
+      using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+      using word_type   = typename policy_type::word_type;
+
+      // Filter properties
+      auto constexpr word_size       = sizeof(word_type);
+      auto constexpr words_per_block = policy_type::words_per_block;
+
+      rmm::device_buffer results{num_row_groups, stream, mr};
+
+      // Query literal in bloom filters.
+      thrust::for_each(
+        rmm::exec_policy(stream),
+        thrust::make_counting_iterator<size_t>(0),
+        thrust::make_counting_iterator(num_row_groups),
+        [buffer_ptrs          = buffer_ptrs.data(),
+         buffer_sizes         = buffer_sizes.data(),
+         d_scalar             = literal->get_value(),
+         col_idx              = equality_col_idx,
+         num_equality_columns = num_equality_columns,
+         results = reinterpret_cast<bool*>(results.data())] __device__(auto row_group_idx) {
+          // Filter bitset buffer index
+          auto const filter_idx = col_idx + (num_equality_columns * row_group_idx);
+          // Bitset ptr must be a non-const to be used in bloom_filter_ref.
+          auto bitset_ptr              = reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]);
+          auto const num_filter_blocks = buffer_sizes[filter_idx] / (word_size * words_per_block);
+
+          // Create a bloom filter view
+          cuco::bloom_filter_ref<key_type,
+                                 cuco::extent<std::size_t>,
+                                 cuco::thread_scope_device,
+                                 policy_type>
+            filter{bitset_ptr,
+                   num_filter_blocks,
+                   {},  // scope
+                   {hasher_type{0}}};
+
+          // Query the bloom filter and store results
+          results[row_group_idx] = filter.contains(d_scalar.value<T>());
+        });
+
+      return std::make_unique<cudf::column>(cudf::data_type{cudf::type_id::BOOL8},
+                                            static_cast<cudf::size_type>(num_row_groups),
+                                            std::move(results),
+                                            rmm::device_buffer{},
+                                            0);
     }
-  };
-
-  // MH: Remove me. Bitwise validation for bloom filter
-  validate_filter_bitwise(stream);
-
-  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
-}
+  }
+};
 
 /**
- * @brief Collects column indices with an equality predicate in the AST expression.
- * This is used in row group filtering based on bloom filters.
+ * @brief Collects lists of equality predicate  literals in the AST expression, one list per input
+ * table column. This is used in row group filtering based on bloom filters.
  */
-class equality_predicate_converter : public ast::detail::expression_transformer {
+class equality_literals_collector : public ast::detail::expression_transformer {
  public:
-  equality_predicate_converter(ast::expression const& expr, size_type const& num_columns)
+  equality_literals_collector() = default;
+
+  equality_literals_collector(ast::expression const& expr, cudf::size_type num_columns)
     : _num_columns{num_columns}
   {
+    _equality_literals.resize(_num_columns);
     expr.accept(*this);
   }
 
@@ -380,7 +185,13 @@ class equality_predicate_converter : public ast::detail::expression_transformer
       CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
                    "Second operand of binary operation with column reference must be a literal");
       v->accept(*this);
-      if (op == ast_operator::EQUAL) { equality_col_idx.emplace_back(v->get_column_index()); }
+
+      // Push to the corresponding column's literals list if equality predicate seen
+      if (op == ast_operator::EQUAL) {
+        auto const col_idx = v->get_column_index();
+        _equality_literals[col_idx].emplace_back(
+          const_cast<ast::literal*>(dynamic_cast<ast::literal const*>(&operands[1].get())));
+      }
     } else {
       auto new_operands = visit_operands(operands);
       if (cudf::ast::detail::ast_operator_arity(op) == 2) {
@@ -394,16 +205,16 @@ class equality_predicate_converter : public ast::detail::expression_transformer
   }
 
   /**
-   * @brief Returns a list of column indices with an equality predicate in the AST expression.
+   * @brief Vectors of equality literals in the AST expression, one per input table column
    *
-   * @return List of column indices
+   * @return Vectors of equality literals, one per input table column
    */
-  [[nodiscard]] std::vector<cudf::size_type> get_equality_col_idx() const
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() const
   {
-    return equality_col_idx;
+    return _equality_literals;
   }
 
- private:
+ protected:
   std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
     cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
   {
@@ -415,67 +226,218 @@ class equality_predicate_converter : public ast::detail::expression_transformer
     return transformed_operands;
   }
   std::optional<std::reference_wrapper<ast::expression const>> _equality_expr;
-  std::vector<cudf::size_type> equality_col_idx;
-  size_type _num_columns;
+  std::vector<std::vector<ast::literal*>> _equality_literals;
   std::list<ast::column_reference> _col_ref;
   std::list<ast::operation> _operators;
+  size_type _num_columns;
 };
 
-}  // namespace
+/**
+ * @brief Collects column indices with an equality predicate in the AST expression.
+ * This is used in row group filtering based on bloom filters.
+ */
+class equality_predicate_evaluator : public equality_literals_collector {
+ public:
+  equality_predicate_evaluator(ast::expression const& expr,
+                               size_type num_columns,
+                               std::vector<std::vector<ast::literal*>> const& equality_literals)
+  {
+    // Set the num columns and equality literals
+    _num_columns       = num_columns;
+    _equality_literals = std::move(equality_literals);
+
+    // Compute and store columns literals offsets
+    _col_literals_offsets.reserve(_num_columns + 1);
+    _col_literals_offsets.emplace_back(0);
+
+    std::transform(equality_literals.begin(),
+                   equality_literals.end(),
+                   std::back_inserter(_col_literals_offsets),
+                   [&](auto const& col_literal_map) {
+                     return _col_literals_offsets.back() +
+                            static_cast<cudf::size_type>(col_literal_map.size());
+                   });
+
+    // Add this visitor
+    expr.accept(*this);
+  }
 
-std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::apply_bloom_filters(
+  /**
+   * @brief Delete equality literals getter
+   */
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() = delete;
+
+  // Bring all overloads of `visit` from equality_predicate_collector into scope
+  using equality_literals_collector::visit;
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override
+  {
+    using cudf::ast::ast_operator;
+    auto const operands = expr.get_operands();
+    auto const op       = expr.get_operator();
+
+    if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
+      // First operand should be column reference, second should be literal.
+      CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
+                   "Only binary operations are supported on column reference");
+      CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
+                   "Second operand of binary operation with column reference must be a literal");
+      v->accept(*this);
+
+      if (op == ast_operator::EQUAL) {
+        auto const literal_ptr =
+          const_cast<ast::literal*>(dynamic_cast<ast::literal const*>(&operands[1].get()));
+        auto const col_idx            = v->get_column_index();
+        auto const& equality_literals = _equality_literals[col_idx];
+        auto col_ref_offset           = _col_literals_offsets[col_idx];
+        auto const ptr =
+          std::find(equality_literals.cbegin(), equality_literals.cend(), literal_ptr);
+        CUDF_EXPECTS(ptr != equality_literals.end(), "Could not find the literal ptr");
+        col_ref_offset += std::distance(equality_literals.cbegin(), ptr);
+
+        auto const& value = _col_ref.emplace_back(col_ref_offset);
+        auto const& op    = _operators.emplace_back(ast_operator::NOT, value);
+        _operators.emplace_back(ast_operator::NOT, op);
+      }
+    } else {
+      auto new_operands = visit_operands(operands);
+      if (cudf::ast::detail::ast_operator_arity(op) == 2) {
+        _operators.emplace_back(op, new_operands.front(), new_operands.back());
+      } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
+        _operators.emplace_back(op, new_operands.front());
+      }
+    }
+    _equality_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    return std::reference_wrapper<ast::expression const>(_operators.back());
+  }
+
+  /**
+   * @brief Returns the AST to apply on bloom filters
+   *
+   * @return AST operation expression
+   */
+  [[nodiscard]] std::reference_wrapper<ast::expression const> get_equality_expr() const
+  {
+    return _equality_expr.value().get();
+  }
+
+ private:
+  std::vector<cudf::size_type> _col_literals_offsets;
+};
+
+/**
+ * @brief Asynchronously reads bloom filters to device.
+ *
+ * @param sources Dataset sources
+ * @param num_chunks Number of total column chunks to read
+ * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
+ * @param bloom_filter_offsets Bloom filter offsets for all chunks
+ * @param bloom_filter_sizes Bloom filter sizes for all chunks
+ * @param chunk_source_map Association between each column chunk and its source
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ *
+ * @return A future object for reading synchronization
+ */
+std::future<void> read_bloom_filters_async(
   host_span<std::unique_ptr<datasource> const> sources,
-  host_span<std::vector<size_type> const> row_group_indices,
-  host_span<data_type const> output_dtypes,
-  host_span<int const> output_column_schemas,
-  std::reference_wrapper<ast::expression const> filter,
-  rmm::cuda_stream_view stream) const
+  size_t num_chunks,
+  cudf::host_span<rmm::device_buffer> bloom_filter_data,
+  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
+  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
+  std::vector<size_type> const& chunk_source_map,
+  rmm::cuda_stream_view stream)
 {
-  auto const num_cols = output_dtypes.size();
-  CUDF_EXPECTS(output_dtypes.size() == output_column_schemas.size(),
-               "Mismatched size between lists of output column dtypes and output column schema");
-  auto mr = cudf::get_current_device_resource_ref();
-  std::vector<std::unique_ptr<column>> cols;
-  // MH: How do I test for nested or non-comparable columns here?
-  cols.emplace_back(cudf::make_numeric_column(
-    data_type{cudf::type_id::INT32}, num_cols, rmm::device_buffer{}, 0, stream, mr));
+  // Read tasks for bloom filter data
+  std::vector<std::future<size_t>> read_tasks;
 
-  auto mutable_col_idx = cols.back()->mutable_view();
+  // Read bloom filters for all column chunks
+  std::for_each(
+    thrust::make_counting_iterator<size_t>(0),
+    thrust::make_counting_iterator<size_t>(num_chunks),
+    [&](auto const chunk) {
+      // Read bloom filter if present
+      if (bloom_filter_offsets[chunk].has_value()) {
+        auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
+        // If Bloom filter size (header + bitset) is available, just read the entire thing.
+        // Else just read 256 bytes which will contain the entire header and may contain the
+        // entire bitset as well.
+        auto constexpr bloom_filter_size_guess = 256;
+        auto const initial_read_size =
+          static_cast<size_t>(bloom_filter_sizes[chunk].value_or(bloom_filter_size_guess));
 
-  thrust::sequence(rmm::exec_policy(stream),
-                   mutable_col_idx.begin<size_type>(),
-                   mutable_col_idx.end<size_type>(),
-                   0);
+        // Read an initial buffer from source
+        auto& source = sources[chunk_source_map[chunk]];
+        auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
 
-  auto equality_table = cudf::table(std::move(cols));
+        // Deserialize the Bloom filter header from the buffer.
+        BloomFilterHeader header;
+        CompactProtocolReader cp{buffer->data(), buffer->size()};
+        cp.read(&header);
 
-  // Converts AST to EqualityAST with reference to min, max columns in above `stats_table`.
-  equality_predicate_converter equality_expr{filter.get(), static_cast<size_type>(num_cols)};
-  auto equality_col_schemas = equality_expr.get_equality_col_idx();
+        // Test if header is valid.
+        auto const is_header_valid =
+          (header.num_bytes % 32) == 0 and
+          header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
+          header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
+          header.hash.hash == BloomFilterHash::Hash::XXHASH;
 
-  // Convert column indices to column schema indices
-  std::for_each(equality_col_schemas.begin(), equality_col_schemas.end(), [&](auto& col_idx) {
-    col_idx = output_column_schemas[col_idx];
-  });
+        // Do not read if the bloom filter is invalid
+        if (not is_header_valid) {
+          CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
+          return;
+        }
 
-  std::ignore = read_bloom_filters(sources, row_group_indices, equality_col_schemas, stream);
+        // Bloom filter header size
+        auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
+        size_t const bitset_size            = header.num_bytes;
 
-  return std::nullopt;
+        // Check if we already read in the filter bitset in the initial read.
+        if (initial_read_size >= bloom_filter_header_size + bitset_size) {
+          bloom_filter_data[chunk] =
+            rmm::device_buffer{buffer->data() + bloom_filter_header_size, bitset_size, stream};
+        }
+        // Read the bitset from datasource.
+        else {
+          auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
+          // Directly read to device if preferred
+          if (source->is_device_read_preferred(bitset_size)) {
+            bloom_filter_data[chunk] = rmm::device_buffer{bitset_size, stream};
+            auto future_read_size =
+              source->device_read_async(bitset_offset,
+                                        bitset_size,
+                                        static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
+                                        stream);
+
+            read_tasks.emplace_back(std::move(future_read_size));
+          } else {
+            buffer                   = source->host_read(bitset_offset, bitset_size);
+            bloom_filter_data[chunk] = rmm::device_buffer{buffer->data(), buffer->size(), stream};
+          }
+        }
+      }
+    });
+
+  auto sync_fn = [](decltype(read_tasks) read_tasks) {
+    for (auto& task : read_tasks) {
+      task.wait();
+    }
+  };
+
+  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
 }
 
+}  // namespace
+
 std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
   host_span<int const> column_schemas,
+  size_type num_row_groups,
   rmm::cuda_stream_view stream) const
 {
-  // Number of total row groups to process.
-  auto const num_row_groups = std::accumulate(
-    row_group_indices.begin(),
-    row_group_indices.end(),
-    size_t{0},
-    [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
-
   // Descriptors for all the chunks that make up the selected columns
   auto const num_input_columns = column_schemas.size();
   auto const num_chunks        = num_row_groups * num_input_columns;
@@ -518,7 +480,7 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   if (std::any_of(bloom_filter_offsets.cbegin(),
                   bloom_filter_offsets.cend(),
                   [](auto const offset) { return offset.has_value(); })) {
-    // Create a vector to store bloom filter data
+    // Vector to hold bloom filter data
     std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
 
     // Wait on bloom filter read tasks
@@ -530,10 +492,145 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
                              chunk_source_map,
                              stream)
       .wait();
-    // Return the vector
+
+    // Return bloom filter data
     return bloom_filter_data;
   }
+
+  // Return empty vector
   return {};
 }
 
+std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::apply_bloom_filters(
+  host_span<std::unique_ptr<datasource> const> sources,
+  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<data_type const> output_dtypes,
+  host_span<int const> output_column_schemas,
+  std::reference_wrapper<ast::expression const> filter,
+  rmm::cuda_stream_view stream) const
+{
+  auto const num_cols = static_cast<cudf::size_type>(output_dtypes.size());
+  CUDF_EXPECTS(output_dtypes.size() == output_column_schemas.size(),
+               "Mismatched size between lists of output column dtypes and output column schema");
+  auto mr = cudf::get_current_device_resource_ref();
+
+  // Number of total row groups to process.
+  auto const num_row_groups = std::accumulate(
+    row_group_indices.begin(),
+    row_group_indices.end(),
+    size_t{0},
+    [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
+
+  // Collect equality literals for each input table column
+  auto const equality_literals =
+    equality_literals_collector{filter.get(), num_cols}.get_equality_literals();
+
+  std::vector<cudf::size_type> equality_col_schemas;
+  // Convert column indices to column schema indices
+  std::for_each(thrust::make_counting_iterator<size_t>(0),
+                thrust::make_counting_iterator(output_column_schemas.size()),
+                [&](auto col_idx) {
+                  // Only for columns that have a non-empty list of literals associated with it
+                  if (equality_literals[col_idx].size()) {
+                    equality_col_schemas.emplace_back(output_column_schemas[col_idx]);
+                  }
+                });
+
+  // Return early if no equality column
+  if (equality_col_schemas.empty()) { return {}; }
+
+  auto bloom_filter_data =
+    read_bloom_filters(sources, row_group_indices, equality_col_schemas, num_row_groups, stream);
+
+  // No bloom filter buffers, return the original row group indices
+  if (not bloom_filter_data.size()) { return {}; }
+
+  // Copy bitset buffer pointers and sizes to device for querying
+  std::vector<void*> h_buffer_ptrs(bloom_filter_data.size());
+  std::vector<size_t> h_buffer_sizes(bloom_filter_data.size());
+  std::for_each(thrust::make_counting_iterator<size_t>(0),
+                thrust::make_counting_iterator<size_t>(bloom_filter_data.size()),
+                [&](auto i) {
+                  auto const& buffer = bloom_filter_data[i];
+                  h_buffer_ptrs[i]   = const_cast<void*>(buffer.data());
+                  h_buffer_sizes[i]  = buffer.size();
+                });
+
+  auto buffer_ptrs  = cudf::detail::make_device_uvector_async(h_buffer_ptrs, stream, mr);
+  auto buffer_sizes = cudf::detail::make_device_uvector_async(h_buffer_sizes, stream, mr);
+
+  // Create a bloom filter table caster
+  bloom_filter_caster bloom_filter_col{num_row_groups, equality_col_schemas.size()};
+
+  // Create a table
+  std::vector<std::unique_ptr<column>> columns;
+
+  size_t idx = 0;
+  for (size_t col_idx = 0; col_idx < output_dtypes.size(); col_idx++) {
+    if (equality_literals[col_idx].empty()) { continue; }
+    auto const& dtype = output_dtypes[col_idx];
+
+    // Only comparable types except fixed point are supported.
+    if (cudf::is_compound(dtype) and dtype.id() != cudf::type_id::STRING) { continue; }
+
+    auto& literals = equality_literals[col_idx];
+    for (ast::literal* const& literal : literals) {
+      columns.push_back(cudf::type_dispatcher<dispatch_storage_type>(
+        dtype, bloom_filter_col, buffer_ptrs, buffer_sizes, idx, dtype, literal, stream, mr));
+    }
+    idx++;
+  }
+
+  auto equality_table = cudf::table(std::move(columns));
+
+  // Make another expression converter but provide the literal map.
+  equality_predicate_evaluator equality_expr{filter.get(), num_cols, equality_literals};
+
+  auto equality_ast  = equality_expr.get_equality_expr();
+  auto predicate_col = cudf::detail::compute_column(equality_table, equality_ast.get(), stream, mr);
+  auto predicate     = predicate_col->view();
+  CUDF_EXPECTS(predicate.type().id() == cudf::type_id::BOOL8,
+               "Filter expression must return a boolean column");
+
+  auto const host_bitmask = [&] {
+    auto const num_bitmasks = num_bitmask_words(predicate.size());
+    if (predicate.nullable()) {
+      return cudf::detail::make_host_vector_sync(
+        device_span<bitmask_type const>(predicate.null_mask(), num_bitmasks), stream);
+    } else {
+      auto bitmask = cudf::detail::make_host_vector<bitmask_type>(num_bitmasks, stream);
+      std::fill(bitmask.begin(), bitmask.end(), ~bitmask_type{0});
+      return bitmask;
+    }
+  }();
+
+  auto validity_it = cudf::detail::make_counting_transform_iterator(
+    0, [bitmask = host_bitmask.data()](auto bit_index) { return bit_is_set(bitmask, bit_index); });
+
+  auto const is_row_group_required = cudf::detail::make_host_vector_sync(
+    device_span<uint8_t const>(predicate.data<uint8_t>(), predicate.size()), stream);
+
+  // Return only filtered row groups based on predicate
+  // if all are required or all are nulls, return.
+  if (predicate.null_count() == predicate.size() or std::all_of(is_row_group_required.cbegin(),
+                                                                is_row_group_required.cend(),
+                                                                [](auto i) { return bool(i); })) {
+    return std::nullopt;
+  }
+  size_type is_required_idx = 0;
+  std::vector<std::vector<size_type>> filtered_row_group_indices;
+  for (auto const& input_row_group_index : row_group_indices) {
+    std::vector<size_type> filtered_row_groups;
+    for (auto const rg_idx : input_row_group_index) {
+      if ((!validity_it[is_required_idx]) || is_row_group_required[is_required_idx]) {
+        filtered_row_groups.push_back(rg_idx);
+      }
+      ++is_required_idx;
+    }
+    filtered_row_group_indices.push_back(std::move(filtered_row_groups));
+  }
+
+  return {filtered_row_group_indices};
+}
+
 }  // namespace cudf::io::parquet::detail
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index eb30cc6955a..2c6eea37c13 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -475,10 +475,9 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
 
   // Return only filtered row groups based on predicate
   // if all are required or all are nulls, return.
-  if (std::all_of(is_row_group_required.cbegin(),
-                  is_row_group_required.cend(),
-                  [](auto i) { return bool(i); }) or
-      predicate.null_count() == predicate.size()) {
+  if (predicate.null_count() == predicate.size() or std::all_of(is_row_group_required.cbegin(),
+                                                                is_row_group_required.cend(),
+                                                                [](auto i) { return bool(i); })) {
     // Call with input_row_group_indices
     return apply_bloom_filters(
       sources, input_row_group_indices, output_dtypes, output_column_schemas, filter, stream);
@@ -498,8 +497,6 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
   // Call with filtered_row_group_indices
   return apply_bloom_filters(
     sources, filtered_row_group_indices, output_dtypes, output_column_schemas, filter, stream);
-
-  return {std::move(filtered_row_group_indices)};
 }
 
 // convert column named expression to column index reference expression
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 75edfdb7f7b..4a30b8b4593 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -195,6 +195,26 @@ class aggregate_reader_metadata {
    */
   void column_info_for_row_group(row_group_info& rg_info, size_type chunk_start_row) const;
 
+  /**
+   * @brief Reads bloom filter bitsets for the specified columns from the given lists of row
+   * groups.
+   *
+   * @param sources Dataset sources
+   * @param row_group_indices Lists of row groups to read bloom filters from, one per source
+   * @param[out] bloom_filter_data List of bloom filter data device buffers
+   * @param column_schemas Schema indices of columns whose bloom filters will be read
+   * @param stream CUDA stream used for device memory operations and kernel launches
+   *
+   * @return A flattened list of bloom filter bitset device buffers for each equality column in each
+   * row group
+   */
+  [[nodiscard]] std::vector<rmm::device_buffer> read_bloom_filters(
+    host_span<std::unique_ptr<datasource> const> sources,
+    host_span<std::vector<size_type> const> row_group_indices,
+    host_span<int const> column_schemas,
+    size_type num_row_groups,
+    rmm::cuda_stream_view stream) const;
+
  public:
   aggregate_reader_metadata(host_span<std::unique_ptr<datasource> const> sources,
                             bool use_arrow_schema,
@@ -386,24 +406,6 @@ class aggregate_reader_metadata {
                     std::optional<std::reference_wrapper<ast::expression const>> filter,
                     rmm::cuda_stream_view stream) const;
 
-  /**
-   * @brief Reads bloom filter bitsets for the specified columns from the given lists of row
-   * groups.
-   *
-   * @param sources Dataset sources
-   * @param row_group_indices Lists of row groups to read bloom filters from, one per source
-   * @param column_schemas Schema indices of columns whose bloom filters will be read
-   * @param stream CUDA stream used for device memory operations and kernel launches
-   *
-   * @return A list of bloom filter bitset device buffers flattened over column schemas over lists
-   * of row group indices
-   */
-  std::vector<rmm::device_buffer> read_bloom_filters(
-    host_span<std::unique_ptr<datasource> const> sources,
-    host_span<std::vector<size_type> const> row_group_indices,
-    host_span<int const> column_schemas,
-    rmm::cuda_stream_view stream) const;
-
   /**
    * @brief Filters and reduces down to a selection of columns
    *

From b477d2d025924a213f8d64aa028194808da91fde Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 26 Nov 2024 07:10:58 +0000
Subject: [PATCH 28/82] Significant code refactoring

---
 cpp/src/io/parquet/bloom_filter_reader.cu  | 212 +++++++++------------
 cpp/src/io/parquet/predicate_pushdown.cpp  | 114 ++++++-----
 cpp/src/io/parquet/reader_impl_helpers.hpp |  21 +-
 3 files changed, 181 insertions(+), 166 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index ecf59238a49..5866c42075c 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -53,30 +53,31 @@ namespace {
  *
  */
 struct bloom_filter_caster {
+  cudf::device_span<void* const> buffer_ptrs;
+  cudf::device_span<size_t const> buffer_sizes;
   size_t num_row_groups;
   size_t num_equality_columns;
 
-  // Creates device columns from column statistics (min, max)
+  // Creates device columns from bloom filter membership
   template <typename T>
-  std::unique_ptr<cudf::column> operator()(cudf::device_span<void* const> buffer_ptrs,
-                                           cudf::device_span<size_t const> buffer_sizes,
-                                           cudf::size_type equality_col_idx,
+  std::unique_ptr<cudf::column> operator()(cudf::size_type equality_col_idx,
                                            cudf::data_type dtype,
                                            ast::literal* const& literal,
                                            rmm::cuda_stream_view stream,
                                            rmm::device_async_resource_ref mr) const
   {
     // List, Struct, Dictionary types are not supported
-    if constexpr (cudf::is_compound<T>() && !std::is_same_v<T, string_view>) {
+    if constexpr (cudf::is_compound<T>() and not std::is_same_v<T, string_view>) {
       CUDF_FAIL("Compound types don't support equality predicate");
     } else {
-      CUDF_EXPECTS(dtype.id() == literal->get_data_type().id(), "Mismatched data_types");
-
       using key_type    = T;
       using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
       using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
       using word_type   = typename policy_type::word_type;
 
+      // Check if the literal has the same type as the column
+      CUDF_EXPECTS(dtype.id() == literal->get_data_type().id(), "Mismatched data_types");
+
       // Filter properties
       auto constexpr word_size       = sizeof(word_type);
       auto constexpr words_per_block = policy_type::words_per_block;
@@ -85,7 +86,7 @@ struct bloom_filter_caster {
 
       // Query literal in bloom filters.
       thrust::for_each(
-        rmm::exec_policy(stream),
+        rmm::exec_policy_nosync(stream),
         thrust::make_counting_iterator<size_t>(0),
         thrust::make_counting_iterator(num_row_groups),
         [buffer_ptrs          = buffer_ptrs.data(),
@@ -95,20 +96,19 @@ struct bloom_filter_caster {
          num_equality_columns = num_equality_columns,
          results = reinterpret_cast<bool*>(results.data())] __device__(auto row_group_idx) {
           // Filter bitset buffer index
-          auto const filter_idx = col_idx + (num_equality_columns * row_group_idx);
-          // Bitset ptr must be a non-const to be used in bloom_filter_ref.
-          auto bitset_ptr              = reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]);
+          auto const filter_idx        = col_idx + (num_equality_columns * row_group_idx);
           auto const num_filter_blocks = buffer_sizes[filter_idx] / (word_size * words_per_block);
 
-          // Create a bloom filter view
+          // Create a bloom filter view.
           cuco::bloom_filter_ref<key_type,
                                  cuco::extent<std::size_t>,
-                                 cuco::thread_scope_device,
+                                 cuco::thread_scope_thread,
                                  policy_type>
-            filter{bitset_ptr,
+            filter{reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]),
                    num_filter_blocks,
-                   {},  // scope
-                   {hasher_type{0}}};
+                   {},   // thread scope since the same literal is being search across different
+                         // bitsets per thread
+                   {}};  // Arrow policy with default xxhash_64, seed = 0 for Arrow compatiblity
 
           // Query the bloom filter and store results
           results[row_group_idx] = filter.contains(d_scalar.value<T>());
@@ -131,10 +131,10 @@ class equality_literals_collector : public ast::detail::expression_transformer {
  public:
   equality_literals_collector() = default;
 
-  equality_literals_collector(ast::expression const& expr, cudf::size_type num_columns)
-    : _num_columns{num_columns}
+  equality_literals_collector(ast::expression const& expr, cudf::size_type num_input_columns)
+    : _num_input_columns{num_input_columns}
   {
-    _equality_literals.resize(_num_columns);
+    _equality_literals.resize(_num_input_columns);
     expr.accept(*this);
   }
 
@@ -154,7 +154,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
   {
     CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
                  "Equality AST supports only left table");
-    CUDF_EXPECTS(expr.get_column_index() < _num_columns,
+    CUDF_EXPECTS(expr.get_column_index() < _num_input_columns,
                  "Column index cannot be more than number of columns in the table");
     _equality_expr = std::reference_wrapper<ast::expression const>(expr);
     return expr;
@@ -229,25 +229,26 @@ class equality_literals_collector : public ast::detail::expression_transformer {
   std::vector<std::vector<ast::literal*>> _equality_literals;
   std::list<ast::column_reference> _col_ref;
   std::list<ast::operation> _operators;
-  size_type _num_columns;
+  size_type _num_input_columns;
 };
 
 /**
- * @brief Collects column indices with an equality predicate in the AST expression.
- * This is used in row group filtering based on bloom filters.
+ * @brief Converts AST expression to bloom filter membership (BloomfilterAST) expression .
+ * This is used in row group filtering based on equality predicate.
  */
-class equality_predicate_evaluator : public equality_literals_collector {
+class bloom_filter_expression_converter : public equality_literals_collector {
  public:
-  equality_predicate_evaluator(ast::expression const& expr,
-                               size_type num_columns,
-                               std::vector<std::vector<ast::literal*>> const& equality_literals)
+  bloom_filter_expression_converter(
+    ast::expression const& expr,
+    size_type num_input_columns,
+    std::vector<std::vector<ast::literal*>> const& equality_literals)
   {
     // Set the num columns and equality literals
-    _num_columns       = num_columns;
+    _num_input_columns = num_input_columns;
     _equality_literals = std::move(equality_literals);
 
     // Compute and store columns literals offsets
-    _col_literals_offsets.reserve(_num_columns + 1);
+    _col_literals_offsets.reserve(_num_input_columns + 1);
     _col_literals_offsets.emplace_back(0);
 
     std::transform(equality_literals.begin(),
@@ -263,7 +264,7 @@ class equality_predicate_evaluator : public equality_literals_collector {
   }
 
   /**
-   * @brief Delete equality literals getter
+   * @brief Delete equality literals getter as no longer needed
    */
   [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() = delete;
 
@@ -329,7 +330,7 @@ class equality_predicate_evaluator : public equality_literals_collector {
 };
 
 /**
- * @brief Asynchronously reads bloom filters to device.
+ * @brief Asynchronously reads bloom filters data to device.
  *
  * @param sources Dataset sources
  * @param num_chunks Number of total column chunks to read
@@ -341,7 +342,7 @@ class equality_predicate_evaluator : public equality_literals_collector {
  *
  * @return A future object for reading synchronization
  */
-std::future<void> read_bloom_filters_async(
+std::future<void> read_bloom_filter_data_async(
   host_span<std::unique_ptr<datasource> const> sources,
   size_t num_chunks,
   cudf::host_span<rmm::device_buffer> bloom_filter_data,
@@ -483,14 +484,14 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
     // Vector to hold bloom filter data
     std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
 
-    // Wait on bloom filter read tasks
-    read_bloom_filters_async(sources,
-                             num_chunks,
-                             bloom_filter_data,
-                             bloom_filter_offsets,
-                             bloom_filter_sizes,
-                             chunk_source_map,
-                             stream)
+    // Wait on bloom filter data read tasks
+    read_bloom_filter_data_async(sources,
+                                 num_chunks,
+                                 bloom_filter_data,
+                                 bloom_filter_offsets,
+                                 bloom_filter_sizes,
+                                 chunk_source_map,
+                                 stream)
       .wait();
 
     // Return bloom filter data
@@ -509,12 +510,12 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   std::reference_wrapper<ast::expression const> filter,
   rmm::cuda_stream_view stream) const
 {
-  auto const num_cols = static_cast<cudf::size_type>(output_dtypes.size());
-  CUDF_EXPECTS(output_dtypes.size() == output_column_schemas.size(),
-               "Mismatched size between lists of output column dtypes and output column schema");
+  // Number of input table columns
+  auto const num_input_columns = static_cast<cudf::size_type>(output_dtypes.size());
+
   auto mr = cudf::get_current_device_resource_ref();
 
-  // Number of total row groups to process.
+  // Total number of row groups to process.
   auto const num_row_groups = std::accumulate(
     row_group_indices.begin(),
     row_group_indices.end(),
@@ -523,10 +524,10 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Collect equality literals for each input table column
   auto const equality_literals =
-    equality_literals_collector{filter.get(), num_cols}.get_equality_literals();
+    equality_literals_collector{filter.get(), num_input_columns}.get_equality_literals();
 
+  // Collect schema indices of columns with equality predicate(s)
   std::vector<cudf::size_type> equality_col_schemas;
-  // Convert column indices to column schema indices
   std::for_each(thrust::make_counting_iterator<size_t>(0),
                 thrust::make_counting_iterator(output_column_schemas.size()),
                 [&](auto col_idx) {
@@ -536,101 +537,72 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
                   }
                 });
 
-  // Return early if no equality column
-  if (equality_col_schemas.empty()) { return {}; }
+  // Return early if no column with equality predicate(s)
+  if (equality_col_schemas.empty()) { return std::nullopt; }
 
+  // Read a vector of bloom filter bitset device buffers for all column with equality predicate(s)
+  // across all row groups
   auto bloom_filter_data =
     read_bloom_filters(sources, row_group_indices, equality_col_schemas, num_row_groups, stream);
 
   // No bloom filter buffers, return the original row group indices
-  if (not bloom_filter_data.size()) { return {}; }
+  if (bloom_filter_data.empty()) { return std::nullopt; }
 
-  // Copy bitset buffer pointers and sizes to device for querying
+  // Copy bloom filter bitset buffer pointers and sizes to device
   std::vector<void*> h_buffer_ptrs(bloom_filter_data.size());
   std::vector<size_t> h_buffer_sizes(bloom_filter_data.size());
   std::for_each(thrust::make_counting_iterator<size_t>(0),
                 thrust::make_counting_iterator<size_t>(bloom_filter_data.size()),
                 [&](auto i) {
                   auto const& buffer = bloom_filter_data[i];
-                  h_buffer_ptrs[i]   = const_cast<void*>(buffer.data());
-                  h_buffer_sizes[i]  = buffer.size();
+                  // Bitset ptr must be non-const to be used in cuco::bloom_filter.
+                  h_buffer_ptrs[i]  = const_cast<void*>(buffer.data());
+                  h_buffer_sizes[i] = buffer.size();
                 });
-
   auto buffer_ptrs  = cudf::detail::make_device_uvector_async(h_buffer_ptrs, stream, mr);
   auto buffer_sizes = cudf::detail::make_device_uvector_async(h_buffer_sizes, stream, mr);
 
-  // Create a bloom filter table caster
-  bloom_filter_caster bloom_filter_col{num_row_groups, equality_col_schemas.size()};
+  // Create a bloom filter query table caster.
+  bloom_filter_caster bloom_filter_col{
+    buffer_ptrs, buffer_sizes, num_row_groups, equality_col_schemas.size()};
 
-  // Create a table
+  // Converts bloom filter membership for equality predicate columns to a table
+  // containing a column for each `col[i] == literal` predicate to be evaluated.
+  // The table contains #sources * #column_chunks_per_src rows.
   std::vector<std::unique_ptr<column>> columns;
+  size_t equality_col_idx = 0;
+  std::for_each(thrust::make_counting_iterator<size_t>(0),
+                thrust::make_counting_iterator(output_dtypes.size()),
+                [&](auto input_col_idx) {
+                  auto const& dtype = output_dtypes[input_col_idx];
 
-  size_t idx = 0;
-  for (size_t col_idx = 0; col_idx < output_dtypes.size(); col_idx++) {
-    if (equality_literals[col_idx].empty()) { continue; }
-    auto const& dtype = output_dtypes[col_idx];
-
-    // Only comparable types except fixed point are supported.
-    if (cudf::is_compound(dtype) and dtype.id() != cudf::type_id::STRING) { continue; }
-
-    auto& literals = equality_literals[col_idx];
-    for (ast::literal* const& literal : literals) {
-      columns.push_back(cudf::type_dispatcher<dispatch_storage_type>(
-        dtype, bloom_filter_col, buffer_ptrs, buffer_sizes, idx, dtype, literal, stream, mr));
-    }
-    idx++;
-  }
-
-  auto equality_table = cudf::table(std::move(columns));
-
-  // Make another expression converter but provide the literal map.
-  equality_predicate_evaluator equality_expr{filter.get(), num_cols, equality_literals};
-
-  auto equality_ast  = equality_expr.get_equality_expr();
-  auto predicate_col = cudf::detail::compute_column(equality_table, equality_ast.get(), stream, mr);
-  auto predicate     = predicate_col->view();
-  CUDF_EXPECTS(predicate.type().id() == cudf::type_id::BOOL8,
-               "Filter expression must return a boolean column");
-
-  auto const host_bitmask = [&] {
-    auto const num_bitmasks = num_bitmask_words(predicate.size());
-    if (predicate.nullable()) {
-      return cudf::detail::make_host_vector_sync(
-        device_span<bitmask_type const>(predicate.null_mask(), num_bitmasks), stream);
-    } else {
-      auto bitmask = cudf::detail::make_host_vector<bitmask_type>(num_bitmasks, stream);
-      std::fill(bitmask.begin(), bitmask.end(), ~bitmask_type{0});
-      return bitmask;
-    }
-  }();
-
-  auto validity_it = cudf::detail::make_counting_transform_iterator(
-    0, [bitmask = host_bitmask.data()](auto bit_index) { return bit_is_set(bitmask, bit_index); });
-
-  auto const is_row_group_required = cudf::detail::make_host_vector_sync(
-    device_span<uint8_t const>(predicate.data<uint8_t>(), predicate.size()), stream);
+                  // Skip if no equality literals for this column
+                  if (equality_literals[input_col_idx].empty()) { return; }
 
-  // Return only filtered row groups based on predicate
-  // if all are required or all are nulls, return.
-  if (predicate.null_count() == predicate.size() or std::all_of(is_row_group_required.cbegin(),
-                                                                is_row_group_required.cend(),
-                                                                [](auto i) { return bool(i); })) {
-    return std::nullopt;
-  }
-  size_type is_required_idx = 0;
-  std::vector<std::vector<size_type>> filtered_row_group_indices;
-  for (auto const& input_row_group_index : row_group_indices) {
-    std::vector<size_type> filtered_row_groups;
-    for (auto const rg_idx : input_row_group_index) {
-      if ((!validity_it[is_required_idx]) || is_row_group_required[is_required_idx]) {
-        filtered_row_groups.push_back(rg_idx);
-      }
-      ++is_required_idx;
-    }
-    filtered_row_group_indices.push_back(std::move(filtered_row_groups));
-  }
+                  // Skip if non-comparable (compound) type except string
+                  if (cudf::is_compound(dtype) and dtype.id() != cudf::type_id::STRING) { return; }
 
-  return {filtered_row_group_indices};
+                  // Add a column for all literals associated with an equality column
+                  for (ast::literal* const& literal : equality_literals[input_col_idx]) {
+                    columns.emplace_back(cudf::type_dispatcher<dispatch_storage_type>(
+                      dtype, bloom_filter_col, equality_col_idx, dtype, literal, stream, mr));
+                  }
+                  equality_col_idx++;
+                });
+  auto bloom_filter_membership_table = cudf::table(std::move(columns));
+
+  // Convert AST to BloomfilterAST expression with reference to bloom filter membership
+  // in above `bloom_filter_membership_table`
+  bloom_filter_expression_converter equality_expr{
+    filter.get(), num_input_columns, equality_literals};
+
+  // Filter bloom filter membership table with the BloomfilterAST expression and collect filtered
+  // row group indices
+  return collect_filtered_row_group_indices(bloom_filter_membership_table,
+                                            equality_expr.get_equality_expr(),
+                                            row_group_indices,
+                                            stream,
+                                            mr);
 }
 
 }  // namespace cudf::io::parquet::detail
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index 2c6eea37c13..760b2d18eec 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -400,7 +400,6 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
 {
   auto mr = cudf::get_current_device_resource_ref();
   // Create row group indices.
-  std::vector<std::vector<size_type>> filtered_row_group_indices;
   std::vector<std::vector<size_type>> all_row_group_indices;
   host_span<std::vector<size_type> const> input_row_group_indices;
   if (row_group_indices.empty()) {
@@ -449,54 +448,24 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
 
   // Converts AST to StatsAST with reference to min, max columns in above `stats_table`.
   stats_expression_converter stats_expr{filter.get(), static_cast<size_type>(output_dtypes.size())};
-  auto stats_ast     = stats_expr.get_stats_expr();
-  auto predicate_col = cudf::detail::compute_column(stats_table, stats_ast.get(), stream, mr);
-  auto predicate     = predicate_col->view();
-  CUDF_EXPECTS(predicate.type().id() == cudf::type_id::BOOL8,
-               "Filter expression must return a boolean column");
 
-  auto const host_bitmask = [&] {
-    auto const num_bitmasks = num_bitmask_words(predicate.size());
-    if (predicate.nullable()) {
-      return cudf::detail::make_host_vector_sync(
-        device_span<bitmask_type const>(predicate.null_mask(), num_bitmasks), stream);
-    } else {
-      auto bitmask = cudf::detail::make_host_vector<bitmask_type>(num_bitmasks, stream);
-      std::fill(bitmask.begin(), bitmask.end(), ~bitmask_type{0});
-      return bitmask;
-    }
-  }();
+  // Filter stats table with StatsAST expression and collect filtered row group indices
+  auto filtered_row_group_indices = collect_filtered_row_group_indices(
+    stats_table, stats_expr.get_stats_expr(), row_group_indices, stream, mr);
 
-  auto validity_it = cudf::detail::make_counting_transform_iterator(
-    0, [bitmask = host_bitmask.data()](auto bit_index) { return bit_is_set(bitmask, bit_index); });
+  // Span on row groups to apply bloom filtering on.
+  auto const bloom_filter_input_row_groups =
+    filtered_row_group_indices.has_value()
+      ? host_span<std::vector<size_type> const>(filtered_row_group_indices.value())
+      : input_row_group_indices;
 
-  auto const is_row_group_required = cudf::detail::make_host_vector_sync(
-    device_span<uint8_t const>(predicate.data<uint8_t>(), predicate.size()), stream);
+  // Apply bloom filtering on the bloom filter input row groups
+  auto const bloom_filtered_row_groups = apply_bloom_filters(
+    sources, bloom_filter_input_row_groups, output_dtypes, output_column_schemas, filter, stream);
 
-  // Return only filtered row groups based on predicate
-  // if all are required or all are nulls, return.
-  if (predicate.null_count() == predicate.size() or std::all_of(is_row_group_required.cbegin(),
-                                                                is_row_group_required.cend(),
-                                                                [](auto i) { return bool(i); })) {
-    // Call with input_row_group_indices
-    return apply_bloom_filters(
-      sources, input_row_group_indices, output_dtypes, output_column_schemas, filter, stream);
-  }
-  size_type is_required_idx = 0;
-  for (auto const& input_row_group_index : input_row_group_indices) {
-    std::vector<size_type> filtered_row_groups;
-    for (auto const rg_idx : input_row_group_index) {
-      if ((!validity_it[is_required_idx]) || is_row_group_required[is_required_idx]) {
-        filtered_row_groups.push_back(rg_idx);
-      }
-      ++is_required_idx;
-    }
-    filtered_row_group_indices.push_back(std::move(filtered_row_groups));
-  }
-
-  // Call with filtered_row_group_indices
-  return apply_bloom_filters(
-    sources, filtered_row_group_indices, output_dtypes, output_column_schemas, filter, stream);
+  // Return bloom filtered row group indices iff collected
+  return bloom_filtered_row_groups.has_value() ? bloom_filtered_row_groups
+                                               : filtered_row_group_indices;
 }
 
 // convert column named expression to column index reference expression
@@ -647,4 +616,59 @@ class names_from_expression : public ast::detail::expression_transformer {
   return names_from_expression(expr, skip_names).to_vector();
 }
 
+std::optional<std::vector<std::vector<size_type>>> collect_filtered_row_group_indices(
+  cudf::table_view table,
+  std::reference_wrapper<ast::expression const> expr_ast,
+  host_span<std::vector<size_type> const> input_row_group_indices,
+  rmm::cuda_stream_view stream,
+  rmm::device_async_resource_ref mr)
+{
+  // Filter the input table using equality predicate evaluator
+  auto predicate_col = cudf::detail::compute_column(table, expr_ast.get(), stream, mr);
+  auto predicate     = predicate_col->view();
+  CUDF_EXPECTS(predicate.type().id() == cudf::type_id::BOOL8,
+               "Filter expression must return a boolean column");
+
+  auto const host_bitmask = [&] {
+    auto const num_bitmasks = num_bitmask_words(predicate.size());
+    if (predicate.nullable()) {
+      return cudf::detail::make_host_vector_sync(
+        device_span<bitmask_type const>(predicate.null_mask(), num_bitmasks), stream);
+    } else {
+      auto bitmask = cudf::detail::make_host_vector<bitmask_type>(num_bitmasks, stream);
+      std::fill(bitmask.begin(), bitmask.end(), ~bitmask_type{0});
+      return bitmask;
+    }
+  }();
+
+  auto validity_it = cudf::detail::make_counting_transform_iterator(
+    0, [bitmask = host_bitmask.data()](auto bit_index) { return bit_is_set(bitmask, bit_index); });
+
+  auto const is_row_group_required = cudf::detail::make_host_vector_sync(
+    device_span<uint8_t const>(predicate.data<uint8_t>(), predicate.size()), stream);
+
+  // Return only filtered row groups based on predicate, or all are required, or all are nulls.
+  if (predicate.null_count() == predicate.size() or std::all_of(is_row_group_required.cbegin(),
+                                                                is_row_group_required.cend(),
+                                                                [](auto i) { return bool(i); })) {
+    return std::nullopt;
+  }
+
+  // Collect indices of the filtered row groups
+  size_type is_required_idx = 0;
+  std::vector<std::vector<size_type>> filtered_row_group_indices;
+  for (auto const& input_row_group_index : input_row_group_indices) {
+    std::vector<size_type> filtered_row_groups;
+    for (auto const rg_idx : input_row_group_index) {
+      if ((!validity_it[is_required_idx]) || is_row_group_required[is_required_idx]) {
+        filtered_row_groups.push_back(rg_idx);
+      }
+      ++is_required_idx;
+    }
+    filtered_row_group_indices.push_back(std::move(filtered_row_groups));
+  }
+
+  return {filtered_row_group_indices};
+}
+
 }  // namespace cudf::io::parquet::detail
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 4a30b8b4593..c2ce897ce9b 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -366,7 +366,7 @@ class aggregate_reader_metadata {
    * @param row_group_indices Lists of row groups to read, one per source
    * @param output_dtypes Datatypes of of output columns
    * @param output_column_schemas schema indices of output columns
-   * @param filter AST expression to filter row groups based on Column chunk statistics
+   * @param filter AST expression to filter row groups based on bloom filter membership
    * @param stream CUDA stream used for device memory operations and kernel launches
    *
    * @return Filtered row group indices, if any is filtered.
@@ -489,4 +489,23 @@ class named_to_reference_converter : public ast::detail::expression_transformer
   std::optional<std::reference_wrapper<ast::expression const>> expr,
   std::vector<std::string> const& skip_names);
 
+/**
+ * @brief Filter table using the provided (StatsAST or BloomfilterAST) expression and
+ * collect filtered row group indices
+ *
+ * @param table Table of stats or bloom filter membership columns
+ * @param expr_ast StatsAST or BloomfilterAST expression to evaluate.
+ * @param input_row_group_indices Lists of input row groups to read, one per source
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ * @param mr Device memory resource used to be used in cudf::compute_column
+ *
+ * @return Collected filtered row group indices, if any.
+ */
+[[nodiscard]] std::optional<std::vector<std::vector<size_type>>> collect_filtered_row_group_indices(
+  cudf::table_view ast_table,
+  std::reference_wrapper<ast::expression const> expr_ast,
+  host_span<std::vector<size_type> const> input_row_group_indices,
+  rmm::cuda_stream_view stream,
+  rmm::device_async_resource_ref mr);
+
 }  // namespace cudf::io::parquet::detail

From f9f17469269268c887a2e806ff5af60a870c23cb Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 26 Nov 2024 07:12:24 +0000
Subject: [PATCH 29/82] minor style fix

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 2 +-
 cpp/tests/hashing/bloom_filter_test.cu    | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 5866c42075c..ef59d313505 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -108,7 +108,7 @@ struct bloom_filter_caster {
                    num_filter_blocks,
                    {},   // thread scope since the same literal is being search across different
                          // bitsets per thread
-                   {}};  // Arrow policy with default xxhash_64, seed = 0 for Arrow compatiblity
+                   {}};  // Arrow policy with default xxhash_64, seed = 0 for Arrow compatibility
 
           // Query the bloom filter and store results
           results[row_group_idx] = filter.contains(d_scalar.value<T>());
diff --git a/cpp/tests/hashing/bloom_filter_test.cu b/cpp/tests/hashing/bloom_filter_test.cu
index e0e98dd84a0..c064b3cf0ff 100644
--- a/cpp/tests/hashing/bloom_filter_test.cu
+++ b/cpp/tests/hashing/bloom_filter_test.cu
@@ -92,4 +92,4 @@ TYPED_TEST(BloomFilter_TestTyped, TestStrings)
   // Check
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(output, d_expected);
 }
-*/
\ No newline at end of file
+*/

From bad484f7155223b7002958747cc42222f93e9b8e Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 26 Nov 2024 07:41:21 +0000
Subject: [PATCH 30/82] refactoring

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 37 +++++++++++------------
 1 file changed, 17 insertions(+), 20 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index ef59d313505..a753ed76ba4 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -17,7 +17,6 @@
 #include "arrow_filter_policy.cuh"
 #include "compact_protocol_reader.hpp"
 #include "io/parquet/parquet.hpp"
-#include "io/parquet/parquet_gpu.hpp"
 #include "reader_impl_helpers.hpp"
 
 #include <cudf/ast/detail/expression_transformer.hpp>
@@ -28,6 +27,8 @@
 #include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
 #include <cudf/hashing/detail/xxhash_64.cuh>
+#include <cudf/utilities/span.hpp>
+#include <cudf/utilities/traits.hpp>
 
 #include <rmm/cuda_stream_view.hpp>
 #include <rmm/device_buffer.hpp>
@@ -36,20 +37,16 @@
 
 #include <cuco/bloom_filter_ref.cuh>
 #include <thrust/iterator/counting_iterator.h>
-#include <thrust/logical.h>
-#include <thrust/sequence.h>
 
 #include <future>
-#include <iterator>
 #include <numeric>
 #include <optional>
-#include <random>
 
 namespace cudf::io::parquet::detail {
 namespace {
 
 /**
- * @brief Converts bloom filter query results for column chunks to a device column.
+ * @brief Converts bloom filter membership results for column chunks to a device column.
  *
  */
 struct bloom_filter_caster {
@@ -124,7 +121,7 @@ struct bloom_filter_caster {
 };
 
 /**
- * @brief Collects lists of equality predicate  literals in the AST expression, one list per input
+ * @brief Collects lists of equality predicate literals in the AST expression, one list per input
  * table column. This is used in row group filtering based on bloom filters.
  */
 class equality_literals_collector : public ast::detail::expression_transformer {
@@ -143,7 +140,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
    */
   std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override
   {
-    _equality_expr = std::reference_wrapper<ast::expression const>(expr);
+    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(expr);
     return expr;
   }
 
@@ -153,10 +150,10 @@ class equality_literals_collector : public ast::detail::expression_transformer {
   std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override
   {
     CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
-                 "Equality AST supports only left table");
+                 "BloomfilterAST supports only left table");
     CUDF_EXPECTS(expr.get_column_index() < _num_input_columns,
                  "Column index cannot be more than number of columns in the table");
-    _equality_expr = std::reference_wrapper<ast::expression const>(expr);
+    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(expr);
     return expr;
   }
 
@@ -166,7 +163,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
   std::reference_wrapper<ast::expression const> visit(
     ast::column_name_reference const& expr) override
   {
-    CUDF_FAIL("Column name reference is not supported in equality AST");
+    CUDF_FAIL("Column name reference is not supported in BloomfilterAST");
   }
 
   /**
@@ -186,7 +183,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
                    "Second operand of binary operation with column reference must be a literal");
       v->accept(*this);
 
-      // Push to the corresponding column's literals list if equality predicate seen
+      // Push to the corresponding column's literals list iff equality predicate is seen
       if (op == ast_operator::EQUAL) {
         auto const col_idx = v->get_column_index();
         _equality_literals[col_idx].emplace_back(
@@ -200,7 +197,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
         _operators.emplace_back(op, new_operands.front());
       }
     }
-    _equality_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(_operators.back());
     return std::reference_wrapper<ast::expression const>(_operators.back());
   }
 
@@ -225,7 +222,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
     }
     return transformed_operands;
   }
-  std::optional<std::reference_wrapper<ast::expression const>> _equality_expr;
+  std::optional<std::reference_wrapper<ast::expression const>> _bloom_filter_expr;
   std::vector<std::vector<ast::literal*>> _equality_literals;
   std::list<ast::column_reference> _col_ref;
   std::list<ast::operation> _operators;
@@ -311,18 +308,18 @@ class bloom_filter_expression_converter : public equality_literals_collector {
         _operators.emplace_back(op, new_operands.front());
       }
     }
-    _equality_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(_operators.back());
     return std::reference_wrapper<ast::expression const>(_operators.back());
   }
 
   /**
-   * @brief Returns the AST to apply on bloom filters
+   * @brief Returns the AST to apply on bloom filters mmebership.
    *
    * @return AST operation expression
    */
-  [[nodiscard]] std::reference_wrapper<ast::expression const> get_equality_expr() const
+  [[nodiscard]] std::reference_wrapper<ast::expression const> get_bloom_filter_expr() const
   {
-    return _equality_expr.value().get();
+    return _bloom_filter_expr.value().get();
   }
 
  private:
@@ -593,13 +590,13 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Convert AST to BloomfilterAST expression with reference to bloom filter membership
   // in above `bloom_filter_membership_table`
-  bloom_filter_expression_converter equality_expr{
+  bloom_filter_expression_converter bloom_filter_expr{
     filter.get(), num_input_columns, equality_literals};
 
   // Filter bloom filter membership table with the BloomfilterAST expression and collect filtered
   // row group indices
   return collect_filtered_row_group_indices(bloom_filter_membership_table,
-                                            equality_expr.get_equality_expr(),
+                                            bloom_filter_expr.get_bloom_filter_expr(),
                                             row_group_indices,
                                             stream,
                                             mr);

From ce09d43ac8dbded82c7d3370f95f67204eaba4fa Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 26 Nov 2024 07:47:06 +0000
Subject: [PATCH 31/82] Minor refactoring

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 115 +++++++++++-----------
 1 file changed, 59 insertions(+), 56 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index a753ed76ba4..91eeba69ca0 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -356,68 +356,71 @@ std::future<void> read_bloom_filter_data_async(
     thrust::make_counting_iterator<size_t>(0),
     thrust::make_counting_iterator<size_t>(num_chunks),
     [&](auto const chunk) {
-      // Read bloom filter if present
-      if (bloom_filter_offsets[chunk].has_value()) {
-        auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
-        // If Bloom filter size (header + bitset) is available, just read the entire thing.
-        // Else just read 256 bytes which will contain the entire header and may contain the
-        // entire bitset as well.
-        auto constexpr bloom_filter_size_guess = 256;
-        auto const initial_read_size =
-          static_cast<size_t>(bloom_filter_sizes[chunk].value_or(bloom_filter_size_guess));
-
-        // Read an initial buffer from source
-        auto& source = sources[chunk_source_map[chunk]];
-        auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
-
-        // Deserialize the Bloom filter header from the buffer.
-        BloomFilterHeader header;
-        CompactProtocolReader cp{buffer->data(), buffer->size()};
-        cp.read(&header);
-
-        // Test if header is valid.
-        auto const is_header_valid =
-          (header.num_bytes % 32) == 0 and
-          header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
-          header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
-          header.hash.hash == BloomFilterHash::Hash::XXHASH;
-
-        // Do not read if the bloom filter is invalid
-        if (not is_header_valid) {
-          CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
-          return;
-        }
+      // Skip if bloom filter offset absent
+      if (not bloom_filter_offsets[chunk].has_value()) { return; }
+
+      // Read bloom filter iff present
+      auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
+
+      // If Bloom filter size (header + bitset) is available, just read the entire thing.
+      // Else just read 256 bytes which will contain the entire header and may contain the
+      // entire bitset as well.
+      auto constexpr bloom_filter_size_guess = 256;
+      auto const initial_read_size =
+        static_cast<size_t>(bloom_filter_sizes[chunk].value_or(bloom_filter_size_guess));
+
+      // Read an initial buffer from source
+      auto& source = sources[chunk_source_map[chunk]];
+      auto buffer  = source->host_read(bloom_filter_offset, initial_read_size);
+
+      // Deserialize the Bloom filter header from the buffer.
+      BloomFilterHeader header;
+      CompactProtocolReader cp{buffer->data(), buffer->size()};
+      cp.read(&header);
+
+      // Check if the bloom filter header is valid.
+      auto const is_header_valid =
+        (header.num_bytes % 32) == 0 and
+        header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
+        header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
+        header.hash.hash == BloomFilterHash::Hash::XXHASH;
+
+      // Do not read if the bloom filter is invalid
+      if (not is_header_valid) {
+        CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
+        return;
+      }
 
-        // Bloom filter header size
-        auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
-        size_t const bitset_size            = header.num_bytes;
+      // Bloom filter header size
+      auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
+      size_t const bitset_size            = static_cast<size_t>(header.num_bytes);
 
-        // Check if we already read in the filter bitset in the initial read.
-        if (initial_read_size >= bloom_filter_header_size + bitset_size) {
-          bloom_filter_data[chunk] =
-            rmm::device_buffer{buffer->data() + bloom_filter_header_size, bitset_size, stream};
-        }
-        // Read the bitset from datasource.
-        else {
-          auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
-          // Directly read to device if preferred
-          if (source->is_device_read_preferred(bitset_size)) {
-            bloom_filter_data[chunk] = rmm::device_buffer{bitset_size, stream};
-            auto future_read_size =
-              source->device_read_async(bitset_offset,
-                                        bitset_size,
-                                        static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
-                                        stream);
-
-            read_tasks.emplace_back(std::move(future_read_size));
-          } else {
-            buffer                   = source->host_read(bitset_offset, bitset_size);
-            bloom_filter_data[chunk] = rmm::device_buffer{buffer->data(), buffer->size(), stream};
-          }
+      // Check if we already read in the filter bitset in the initial read.
+      if (initial_read_size >= bloom_filter_header_size + bitset_size) {
+        bloom_filter_data[chunk] =
+          rmm::device_buffer{buffer->data() + bloom_filter_header_size, bitset_size, stream};
+      }
+      // Read the bitset from datasource.
+      else {
+        auto const bitset_offset = bloom_filter_offset + bloom_filter_header_size;
+        // Directly read to device if preferred
+        if (source->is_device_read_preferred(bitset_size)) {
+          bloom_filter_data[chunk] = rmm::device_buffer{bitset_size, stream};
+          auto future_read_size =
+            source->device_read_async(bitset_offset,
+                                      bitset_size,
+                                      static_cast<uint8_t*>(bloom_filter_data[chunk].data()),
+                                      stream);
+
+          read_tasks.emplace_back(std::move(future_read_size));
+        } else {
+          buffer                   = source->host_read(bitset_offset, bitset_size);
+          bloom_filter_data[chunk] = rmm::device_buffer{buffer->data(), buffer->size(), stream};
         }
       }
     });
 
+  // Read task sync function
   auto sync_fn = [](decltype(read_tasks) read_tasks) {
     for (auto& task : read_tasks) {
       task.wait();

From dddee6ca406f0d4e9e4c0597c329b3b8f899dcf7 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 26 Nov 2024 08:16:25 +0000
Subject: [PATCH 32/82] Minor improvements

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 21 +++++++++++----------
 1 file changed, 11 insertions(+), 10 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 91eeba69ca0..1d9ef7a6742 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -206,7 +206,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
    *
    * @return Vectors of equality literals, one per input table column
    */
-  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() const
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> const get_equality_literals() const
   {
     return _equality_literals;
   }
@@ -286,17 +286,18 @@ class bloom_filter_expression_converter : public equality_literals_collector {
       v->accept(*this);
 
       if (op == ast_operator::EQUAL) {
-        auto const literal_ptr =
-          const_cast<ast::literal*>(dynamic_cast<ast::literal const*>(&operands[1].get()));
+        // Search the literal in this input column's equality literals list and add to the offset.
         auto const col_idx            = v->get_column_index();
         auto const& equality_literals = _equality_literals[col_idx];
-        auto col_ref_offset           = _col_literals_offsets[col_idx];
-        auto const ptr =
-          std::find(equality_literals.cbegin(), equality_literals.cend(), literal_ptr);
-        CUDF_EXPECTS(ptr != equality_literals.end(), "Could not find the literal ptr");
-        col_ref_offset += std::distance(equality_literals.cbegin(), ptr);
-
-        auto const& value = _col_ref.emplace_back(col_ref_offset);
+        auto col_literal_offset       = _col_literals_offsets[col_idx];
+        auto const literal_iter       = std::find(equality_literals.cbegin(),
+                                            equality_literals.cend(),
+                                            dynamic_cast<ast::literal const*>(&operands[1].get()));
+        CUDF_EXPECTS(literal_iter != equality_literals.end(), "Could not find the literal ptr");
+        col_literal_offset += std::distance(equality_literals.cbegin(), literal_iter);
+
+        // Evaluate boolean is_true(value) expression as NOT(NOT(value))
+        auto const& value = _col_ref.emplace_back(col_literal_offset);
         auto const& op    = _operators.emplace_back(ast_operator::NOT, value);
         _operators.emplace_back(ast_operator::NOT, op);
       }

From 0cfeb80a8a413d22c947b9dfa1782c38ac1dca52 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 26 Nov 2024 21:10:48 +0000
Subject: [PATCH 33/82] Add gtest

---
 cpp/src/io/parquet/predicate_pushdown.cpp  |  9 +++---
 cpp/src/io/parquet/reader_impl_helpers.hpp |  4 +--
 cpp/tests/hashing/bloom_filter_test.cu     | 36 ++++++++++------------
 3 files changed, 23 insertions(+), 26 deletions(-)

diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index 760b2d18eec..ba6f690abd3 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -618,13 +618,13 @@ class names_from_expression : public ast::detail::expression_transformer {
 
 std::optional<std::vector<std::vector<size_type>>> collect_filtered_row_group_indices(
   cudf::table_view table,
-  std::reference_wrapper<ast::expression const> expr_ast,
+  std::reference_wrapper<ast::expression const> ast_expr,
   host_span<std::vector<size_type> const> input_row_group_indices,
   rmm::cuda_stream_view stream,
   rmm::device_async_resource_ref mr)
 {
-  // Filter the input table using equality predicate evaluator
-  auto predicate_col = cudf::detail::compute_column(table, expr_ast.get(), stream, mr);
+  // Filter the input table using AST expression
+  auto predicate_col = cudf::detail::compute_column(table, ast_expr.get(), stream, mr);
   auto predicate     = predicate_col->view();
   CUDF_EXPECTS(predicate.type().id() == cudf::type_id::BOOL8,
                "Filter expression must return a boolean column");
@@ -644,10 +644,11 @@ std::optional<std::vector<std::vector<size_type>>> collect_filtered_row_group_in
   auto validity_it = cudf::detail::make_counting_transform_iterator(
     0, [bitmask = host_bitmask.data()](auto bit_index) { return bit_is_set(bitmask, bit_index); });
 
+  // Return only filtered row groups based on predicate
   auto const is_row_group_required = cudf::detail::make_host_vector_sync(
     device_span<uint8_t const>(predicate.data<uint8_t>(), predicate.size()), stream);
 
-  // Return only filtered row groups based on predicate, or all are required, or all are nulls.
+  // Return if all are required, or all are nulls.
   if (predicate.null_count() == predicate.size() or std::all_of(is_row_group_required.cbegin(),
                                                                 is_row_group_required.cend(),
                                                                 [](auto i) { return bool(i); })) {
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index c2ce897ce9b..6cb99a54720 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -494,7 +494,7 @@ class named_to_reference_converter : public ast::detail::expression_transformer
  * collect filtered row group indices
  *
  * @param table Table of stats or bloom filter membership columns
- * @param expr_ast StatsAST or BloomfilterAST expression to evaluate.
+ * @param ast_expr StatsAST or BloomfilterAST expression to filter with.
  * @param input_row_group_indices Lists of input row groups to read, one per source
  * @param stream CUDA stream used for device memory operations and kernel launches
  * @param mr Device memory resource used to be used in cudf::compute_column
@@ -503,7 +503,7 @@ class named_to_reference_converter : public ast::detail::expression_transformer
  */
 [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> collect_filtered_row_group_indices(
   cudf::table_view ast_table,
-  std::reference_wrapper<ast::expression const> expr_ast,
+  std::reference_wrapper<ast::expression const> ast_expr,
   host_span<std::vector<size_type> const> input_row_group_indices,
   rmm::cuda_stream_view stream,
   rmm::device_async_resource_ref mr);
diff --git a/cpp/tests/hashing/bloom_filter_test.cu b/cpp/tests/hashing/bloom_filter_test.cu
index c064b3cf0ff..9ca76c085b6 100644
--- a/cpp/tests/hashing/bloom_filter_test.cu
+++ b/cpp/tests/hashing/bloom_filter_test.cu
@@ -14,13 +14,16 @@
  * limitations under the License.
  */
 
-/*
+// Remove this after cuco bump
+#include "src/io/parquet/arrow_filter_policy.cuh"
+
 #include <cudf_test/base_fixture.hpp>
 #include <cudf_test/column_utilities.hpp>
 #include <cudf_test/column_wrapper.hpp>
 #include <cudf_test/iterator_utilities.hpp>
 
 #include <cudf/detail/cuco_helpers.hpp>
+#include <cudf/hashing.hpp>
 #include <cudf/hashing/detail/xxhash_64.cuh>
 #include <cudf/utilities/default_stream.hpp>
 
@@ -28,19 +31,16 @@
 
 using StringType = cudf::string_view;
 
-template <typename T>
-class BloomFilter_TestTyped : public cudf::test::BaseFixture {};
-
-TYPED_TEST_SUITE(BloomFilter_TestTyped, StringType);
+class BloomFilterTest : public cudf::test::BaseFixture {};
 
-TYPED_TEST(BloomFilter_TestTyped, TestStrings)
+TEST_F(BloomFilterTest, TestStrings)
 {
   using key_type    = StringType;
   using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
   using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+  using word_type   = policy_type::word_type;
 
   std::size_t constexpr num_filter_blocks = 4;
-  std::size_t constexpr num_keys          = 50;
   auto stream                             = cudf::get_default_stream();
 
   // strings data
@@ -64,12 +64,11 @@ TYPED_TEST(BloomFilter_TestTyped, TestStrings)
                      cudf::detail::cuco_allocator<char>>
     filter{num_filter_blocks,
            cuco::thread_scope_device,
-           {hasher_type{0}},
+           {hasher_type{cudf::DEFAULT_HASH_SEED}},
            cudf::detail::cuco_allocator<char>{rmm::mr::polymorphic_allocator<char>{}, stream},
            stream};
 
   // Add strings to the bloom filter
-  auto col = table.column(0);
   filter.add(d_column->begin<key_type>(), d_column->end<key_type>(), stream);
 
   // Number of words in the filter
@@ -78,18 +77,15 @@ TYPED_TEST(BloomFilter_TestTyped, TestStrings)
   auto const output = cudf::column_view{
     cudf::data_type{cudf::type_id::UINT32}, num_words, filter.data(), nullptr, 0, 0, {}};
 
-  using word_type = filter_type::word_type;
-
   // Expected filter bitset words computed using Arrow implementation here:
   // https://godbolt.org/z/oKfqcPWbY
   auto expected = cudf::test::fixed_width_column_wrapper<word_type>(
-    {4194306,    4194305,  2359296,   1073774592, 524544,     1024,       268443648,  8519680,
-     2147500040, 8421380,  269500416, 4202624,    8396802,    100665344,  2147747840, 5243136,
-     131146,     655364,   285345792, 134222340,  545390596,  2281717768, 51201,      41943553,
-     1619656708, 67441680, 8462730,   361220,     2216738864, 587333888,  4219272,    873463873});
-  auto d_expected = cudf::column_device_view::create(expected);
-
-  // Check
-  CUDF_TEST_EXPECT_COLUMNS_EQUAL(output, d_expected);
+    {4194306U,    4194305U,    2359296U,  1073774592U, 524544U,    1024U,      268443648U,
+     8519680U,    2147500040U, 8421380U,  269500416U,  4202624U,   8396802U,   100665344U,
+     2147747840U, 5243136U,    131146U,   655364U,     285345792U, 134222340U, 545390596U,
+     2281717768U, 51201U,      41943553U, 1619656708U, 67441680U,  8462730U,   361220U,
+     2216738864U, 587333888U,  4219272U,  873463873U});
+
+  // Check the bitset for equality
+  CUDF_TEST_EXPECT_COLUMNS_EQUAL(output, expected);
 }
-*/

From 91375850432305ef41fed391d8d99699aa47d731 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 26 Nov 2024 23:20:32 +0000
Subject: [PATCH 34/82] Improvements

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 40 +++++++++++++++++------
 1 file changed, 30 insertions(+), 10 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 1d9ef7a6742..d413a7b6b99 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -26,6 +26,7 @@
 #include <cudf/detail/iterator.cuh>
 #include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
+#include <cudf/hashing.hpp>
 #include <cudf/hashing/detail/xxhash_64.cuh>
 #include <cudf/utilities/span.hpp>
 #include <cudf/utilities/traits.hpp>
@@ -93,7 +94,15 @@ struct bloom_filter_caster {
          num_equality_columns = num_equality_columns,
          results = reinterpret_cast<bool*>(results.data())] __device__(auto row_group_idx) {
           // Filter bitset buffer index
-          auto const filter_idx        = col_idx + (num_equality_columns * row_group_idx);
+          auto const filter_idx = col_idx + (num_equality_columns * row_group_idx);
+
+          // If no bloom filter, then fill in `true` as membership cannot be determined
+          if (buffer_sizes[filter_idx] == 0) {
+            results[row_group_idx] = true;
+            return;
+          }
+
+          // Number of filter blocks
           auto const num_filter_blocks = buffer_sizes[filter_idx] / (word_size * words_per_block);
 
           // Create a bloom filter view.
@@ -101,11 +110,13 @@ struct bloom_filter_caster {
                                  cuco::extent<std::size_t>,
                                  cuco::thread_scope_thread,
                                  policy_type>
-            filter{reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]),
-                   num_filter_blocks,
-                   {},   // thread scope since the same literal is being search across different
-                         // bitsets per thread
-                   {}};  // Arrow policy with default xxhash_64, seed = 0 for Arrow compatibility
+            filter{
+              reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]),
+              num_filter_blocks,
+              cuco::thread_scope_thread,  // Thread scope since the same literal is being search
+                                          // across (read-only) different bitsets per thread
+              {hasher_type{cudf::DEFAULT_HASH_SEED}}};  // Arrow policy with cudf::xxhash_64 seeded
+                                                        // with 0 for Arrow compatibility
 
           // Query the bloom filter and store results
           results[row_group_idx] = filter.contains(d_scalar.value<T>());
@@ -357,9 +368,11 @@ std::future<void> read_bloom_filter_data_async(
     thrust::make_counting_iterator<size_t>(0),
     thrust::make_counting_iterator<size_t>(num_chunks),
     [&](auto const chunk) {
-      // Skip if bloom filter offset absent
-      if (not bloom_filter_offsets[chunk].has_value()) { return; }
-
+      // If bloom filter offset absent, fill in an empty buffer and skip ahead
+      if (not bloom_filter_offsets[chunk].has_value()) {
+        bloom_filter_data[chunk] = {};
+        return;
+      }
       // Read bloom filter iff present
       auto const bloom_filter_offset = bloom_filter_offsets[chunk].value();
 
@@ -379,15 +392,22 @@ std::future<void> read_bloom_filter_data_async(
       CompactProtocolReader cp{buffer->data(), buffer->size()};
       cp.read(&header);
 
+      // Get the hardcoded words_per_block value from `cuco::arrow_filter_policy` using a temporary
+      // `std::byte` key type.
+      auto constexpr words_per_block =
+        cuco::arrow_filter_policy<std::byte,
+                                  cudf::hashing::detail::XXHash_64<std::byte>>::words_per_block;
+
       // Check if the bloom filter header is valid.
       auto const is_header_valid =
-        (header.num_bytes % 32) == 0 and
+        (header.num_bytes % words_per_block) == 0 and
         header.compression.compression == BloomFilterCompression::Compression::UNCOMPRESSED and
         header.algorithm.algorithm == BloomFilterAlgorithm::Algorithm::SPLIT_BLOCK and
         header.hash.hash == BloomFilterHash::Hash::XXHASH;
 
       // Do not read if the bloom filter is invalid
       if (not is_header_valid) {
+        bloom_filter_data[chunk] = {};
         CUDF_LOG_WARN("Encountered an invalid bloom filter header. Skipping");
         return;
       }

From 77152b43cb10f45e57de79f1201c25b92e69a296 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 27 Nov 2024 00:46:31 +0000
Subject: [PATCH 35/82] Support int96 in bloom filter

---
 cpp/src/io/parquet/bloom_filter_reader.cu  | 183 +++++++++++++--------
 cpp/src/io/parquet/reader_impl_helpers.hpp |  14 +-
 2 files changed, 131 insertions(+), 66 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index d413a7b6b99..640ae0d3d22 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -26,7 +26,6 @@
 #include <cudf/detail/iterator.cuh>
 #include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
-#include <cudf/hashing.hpp>
 #include <cudf/hashing/detail/xxhash_64.cuh>
 #include <cudf/utilities/span.hpp>
 #include <cudf/utilities/traits.hpp>
@@ -53,9 +52,85 @@ namespace {
 struct bloom_filter_caster {
   cudf::device_span<void* const> buffer_ptrs;
   cudf::device_span<size_t const> buffer_sizes;
+  host_span<Type const> parquet_types;
   size_t num_row_groups;
   size_t num_equality_columns;
 
+  template <typename T, bool timestamp_is_int96 = false>
+  std::unique_ptr<cudf::column> compute_column(cudf::size_type equality_col_idx,
+                                               cudf::data_type dtype,
+                                               ast::literal* const& literal,
+                                               rmm::cuda_stream_view stream,
+                                               rmm::device_async_resource_ref mr) const
+  {
+    using key_type    = T;
+    using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
+    using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+    using word_type   = typename policy_type::word_type;
+
+    // Check if the literal has the same type as the column
+    CUDF_EXPECTS(dtype.id() == literal->get_data_type().id(), "Mismatched data_types");
+
+    // Filter properties
+    auto constexpr word_size       = sizeof(word_type);
+    auto constexpr words_per_block = policy_type::words_per_block;
+
+    rmm::device_buffer results{num_row_groups, stream, mr};
+
+    // Query literal in bloom filters.
+    thrust::for_each(
+      rmm::exec_policy_nosync(stream),
+      thrust::make_counting_iterator<size_t>(0),
+      thrust::make_counting_iterator(num_row_groups),
+      [buffer_ptrs          = buffer_ptrs.data(),
+       buffer_sizes         = buffer_sizes.data(),
+       d_scalar             = literal->get_value(),
+       col_idx              = equality_col_idx,
+       num_equality_columns = num_equality_columns,
+       results = reinterpret_cast<bool*>(results.data())] __device__(auto row_group_idx) {
+        // Filter bitset buffer index
+        auto const filter_idx = col_idx + (num_equality_columns * row_group_idx);
+
+        // If no bloom filter, then fill in `true` as membership cannot be determined
+        if (buffer_sizes[filter_idx] == 0) {
+          results[row_group_idx] = true;
+          return;
+        }
+
+        // Number of filter blocks
+        auto const num_filter_blocks = buffer_sizes[filter_idx] / (word_size * words_per_block);
+
+        // Create a bloom filter view.
+        cuco::bloom_filter_ref<key_type,
+                               cuco::extent<std::size_t>,
+                               cuco::thread_scope_thread,
+                               policy_type>
+          filter{reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]),
+                 num_filter_blocks,
+                 cuco::thread_scope_thread,  // Thread scope since the same literal is being search
+                                             // across (read-only) different bitsets per thread
+                 {hasher_type{0}}};          // Arrow policy with cudf::xxhash_64
+                                             // seeded with 0 for Arrow compatibility
+
+        // If int96_timestamp type, convert literal to string_view and query bloom
+        // filter
+        if constexpr (cuda::std::is_same_v<T, cudf::string_view> and timestamp_is_int96) {
+          auto const int128_key = static_cast<__int128_t>(d_scalar.value<int64_t>());
+          cudf::string_view probe_key{reinterpret_cast<char const*>(&int128_key), 12};
+          results[row_group_idx] = filter.contains(probe_key);
+        } else {
+          // Query the bloom filter and store results
+          results[row_group_idx] = filter.contains(d_scalar.value<T>());
+        }
+      });
+
+    return std::make_unique<cudf::column>(cudf::data_type{cudf::type_id::BOOL8},
+                                          static_cast<cudf::size_type>(num_row_groups),
+                                          std::move(results),
+                                          rmm::device_buffer{},
+                                          0);
+  }
+
   // Creates device columns from bloom filter membership
   template <typename T>
   std::unique_ptr<cudf::column> operator()(cudf::size_type equality_col_idx,
@@ -67,66 +142,16 @@ struct bloom_filter_caster {
     // List, Struct, Dictionary types are not supported
     if constexpr (cudf::is_compound<T>() and not std::is_same_v<T, string_view>) {
       CUDF_FAIL("Compound types don't support equality predicate");
+    } else if constexpr (cudf::is_timestamp<T>()) {
+      if (parquet_types[equality_col_idx] == Type::INT96) {
+        // For INT96 timestamps, convert to cudf::string_view of 12 bytes
+        return compute_column<cudf::string_view, true>(
+          equality_col_idx, dtype, literal, stream, mr);
+      } else {
+        return compute_column<T>(equality_col_idx, dtype, literal, stream, mr);
+      }
     } else {
-      using key_type    = T;
-      using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
-      using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
-      using word_type   = typename policy_type::word_type;
-
-      // Check if the literal has the same type as the column
-      CUDF_EXPECTS(dtype.id() == literal->get_data_type().id(), "Mismatched data_types");
-
-      // Filter properties
-      auto constexpr word_size       = sizeof(word_type);
-      auto constexpr words_per_block = policy_type::words_per_block;
-
-      rmm::device_buffer results{num_row_groups, stream, mr};
-
-      // Query literal in bloom filters.
-      thrust::for_each(
-        rmm::exec_policy_nosync(stream),
-        thrust::make_counting_iterator<size_t>(0),
-        thrust::make_counting_iterator(num_row_groups),
-        [buffer_ptrs          = buffer_ptrs.data(),
-         buffer_sizes         = buffer_sizes.data(),
-         d_scalar             = literal->get_value(),
-         col_idx              = equality_col_idx,
-         num_equality_columns = num_equality_columns,
-         results = reinterpret_cast<bool*>(results.data())] __device__(auto row_group_idx) {
-          // Filter bitset buffer index
-          auto const filter_idx = col_idx + (num_equality_columns * row_group_idx);
-
-          // If no bloom filter, then fill in `true` as membership cannot be determined
-          if (buffer_sizes[filter_idx] == 0) {
-            results[row_group_idx] = true;
-            return;
-          }
-
-          // Number of filter blocks
-          auto const num_filter_blocks = buffer_sizes[filter_idx] / (word_size * words_per_block);
-
-          // Create a bloom filter view.
-          cuco::bloom_filter_ref<key_type,
-                                 cuco::extent<std::size_t>,
-                                 cuco::thread_scope_thread,
-                                 policy_type>
-            filter{
-              reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]),
-              num_filter_blocks,
-              cuco::thread_scope_thread,  // Thread scope since the same literal is being search
-                                          // across (read-only) different bitsets per thread
-              {hasher_type{cudf::DEFAULT_HASH_SEED}}};  // Arrow policy with cudf::xxhash_64 seeded
-                                                        // with 0 for Arrow compatibility
-
-          // Query the bloom filter and store results
-          results[row_group_idx] = filter.contains(d_scalar.value<T>());
-        });
-
-      return std::make_unique<cudf::column>(cudf::data_type{cudf::type_id::BOOL8},
-                                            static_cast<cudf::size_type>(num_row_groups),
-                                            std::move(results),
-                                            rmm::device_buffer{},
-                                            0);
+      return compute_column<T>(equality_col_idx, dtype, literal, stream, mr);
     }
   }
 };
@@ -523,6 +548,31 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   return {};
 }
 
+std::vector<Type> aggregate_reader_metadata::get_parquet_types(
+  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<int const> column_schemas) const
+{
+  std::vector<Type> parquet_types(column_schemas.size());
+  // Find a source with at least one row group
+  auto const src_iter = std::find_if(row_group_indices.begin(),
+                                     row_group_indices.end(),
+                                     [](auto const& rg) { return rg.size() > 0; });
+  CUDF_EXPECTS(src_iter != row_group_indices.end(), "");
+
+  // Source index
+  auto const src_index = std::distance(row_group_indices.begin(), src_iter);
+  std::transform(column_schemas.begin(),
+                 column_schemas.end(),
+                 parquet_types.begin(),
+                 [&](auto const schema_idx) {
+                   // Use the first row group in this source
+                   auto constexpr row_group_index = 0;
+                   return get_column_metadata(row_group_index, src_index, schema_idx).type;
+                 });
+
+  return parquet_types;
+}
+
 std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::apply_bloom_filters(
   host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
@@ -561,14 +611,17 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   // Return early if no column with equality predicate(s)
   if (equality_col_schemas.empty()) { return std::nullopt; }
 
-  // Read a vector of bloom filter bitset device buffers for all column with equality predicate(s)
-  // across all row groups
+  // Read a vector of bloom filter bitset device buffers for all column with equality
+  // predicate(s) across all row groups
   auto bloom_filter_data =
     read_bloom_filters(sources, row_group_indices, equality_col_schemas, num_row_groups, stream);
 
   // No bloom filter buffers, return the original row group indices
   if (bloom_filter_data.empty()) { return std::nullopt; }
 
+  // Get parquet types for the predicate columns
+  auto const parquet_types = get_parquet_types(row_group_indices, equality_col_schemas);
+
   // Copy bloom filter bitset buffer pointers and sizes to device
   std::vector<void*> h_buffer_ptrs(bloom_filter_data.size());
   std::vector<size_t> h_buffer_sizes(bloom_filter_data.size());
@@ -585,7 +638,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Create a bloom filter query table caster.
   bloom_filter_caster bloom_filter_col{
-    buffer_ptrs, buffer_sizes, num_row_groups, equality_col_schemas.size()};
+    buffer_ptrs, buffer_sizes, parquet_types, num_row_groups, equality_col_schemas.size()};
 
   // Converts bloom filter membership for equality predicate columns to a table
   // containing a column for each `col[i] == literal` predicate to be evaluated.
@@ -617,8 +670,8 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   bloom_filter_expression_converter bloom_filter_expr{
     filter.get(), num_input_columns, equality_literals};
 
-  // Filter bloom filter membership table with the BloomfilterAST expression and collect filtered
-  // row group indices
+  // Filter bloom filter membership table with the BloomfilterAST expression and collect
+  // filtered row group indices
   return collect_filtered_row_group_indices(bloom_filter_membership_table,
                                             bloom_filter_expr.get_bloom_filter_expr(),
                                             row_group_indices,
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 6cb99a54720..c280341ead7 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -205,7 +205,7 @@ class aggregate_reader_metadata {
    * @param column_schemas Schema indices of columns whose bloom filters will be read
    * @param stream CUDA stream used for device memory operations and kernel launches
    *
-   * @return A flattened list of bloom filter bitset device buffers for each equality column in each
+   * @return A flattened list of bloom filter bitset device buffers for each predicate column across
    * row group
    */
   [[nodiscard]] std::vector<rmm::device_buffer> read_bloom_filters(
@@ -215,6 +215,18 @@ class aggregate_reader_metadata {
     size_type num_row_groups,
     rmm::cuda_stream_view stream) const;
 
+  /**
+   * @brief Collects Parquet types for the columns with the specified schema indices
+   *
+   * @param row_group_indices Lists of row groups, once per source
+   * @param column_schemas Schema indices of columns whose types will be collected
+   *
+   * @return A list of parquet types for the columns matching the procided schema indices
+   */
+  [[nodiscard]] std::vector<Type> get_parquet_types(
+    host_span<std::vector<size_type> const> row_group_indices,
+    host_span<int const> column_schemas) const;
+
  public:
   aggregate_reader_metadata(host_span<std::unique_ptr<datasource> const> sources,
                             bool use_arrow_schema,

From 398429124e8989803cae6ccff2bc8a6f559b2f11 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 27 Nov 2024 00:59:42 +0000
Subject: [PATCH 36/82] Cleanup

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 32 +++++++++++------------
 1 file changed, 16 insertions(+), 16 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 640ae0d3d22..df6d48618b0 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -46,7 +46,7 @@ namespace cudf::io::parquet::detail {
 namespace {
 
 /**
- * @brief Converts bloom filter membership results for column chunks to a device column.
+ * @brief Converts bloom filter membership results (for each column chunk) to a device column.
  *
  */
 struct bloom_filter_caster {
@@ -57,11 +57,11 @@ struct bloom_filter_caster {
   size_t num_equality_columns;
 
   template <typename T, bool timestamp_is_int96 = false>
-  std::unique_ptr<cudf::column> compute_column(cudf::size_type equality_col_idx,
-                                               cudf::data_type dtype,
-                                               ast::literal* const& literal,
-                                               rmm::cuda_stream_view stream,
-                                               rmm::device_async_resource_ref mr) const
+  std::unique_ptr<cudf::column> query_bloom_filter(cudf::size_type equality_col_idx,
+                                                   cudf::data_type dtype,
+                                                   ast::literal* const& literal,
+                                                   rmm::cuda_stream_view stream,
+                                                   rmm::device_async_resource_ref mr) const
   {
     using key_type    = T;
     using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
@@ -69,7 +69,8 @@ struct bloom_filter_caster {
     using word_type   = typename policy_type::word_type;
 
     // Check if the literal has the same type as the column
-    CUDF_EXPECTS(dtype.id() == literal->get_data_type().id(), "Mismatched data_types");
+    CUDF_EXPECTS(dtype.id() == literal->get_data_type().id(),
+                 "Mismatched data types between the column and the literal");
 
     // Filter properties
     auto constexpr word_size       = sizeof(word_type);
@@ -77,7 +78,7 @@ struct bloom_filter_caster {
 
     rmm::device_buffer results{num_row_groups, stream, mr};
 
-    // Query literal in bloom filters.
+    // Query literal in bloom filters from each column chunk (row group).
     thrust::for_each(
       rmm::exec_policy_nosync(stream),
       thrust::make_counting_iterator<size_t>(0),
@@ -107,10 +108,9 @@ struct bloom_filter_caster {
                                policy_type>
           filter{reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]),
                  num_filter_blocks,
-                 cuco::thread_scope_thread,  // Thread scope since the same literal is being search
-                                             // across (read-only) different bitsets per thread
-                 {hasher_type{0}}};          // Arrow policy with cudf::xxhash_64
-                                             // seeded with 0 for Arrow compatibility
+                 {},  // Thread scope as the same literal is being searched across different bitsets
+                      // per thread
+                 {}};  // Arrow policy with cudf::XXHash_64 seeded with 0 for Arrow compatibility
 
         // If int96_timestamp type, convert literal to string_view and query bloom
         // filter
@@ -144,14 +144,14 @@ struct bloom_filter_caster {
       CUDF_FAIL("Compound types don't support equality predicate");
     } else if constexpr (cudf::is_timestamp<T>()) {
       if (parquet_types[equality_col_idx] == Type::INT96) {
-        // For INT96 timestamps, convert to cudf::string_view of 12 bytes
-        return compute_column<cudf::string_view, true>(
+        // For INT96 timestamps, use cudf::string_view type and set timestamp_is_int96
+        return query_bloom_filter<cudf::string_view, true>(
           equality_col_idx, dtype, literal, stream, mr);
       } else {
-        return compute_column<T>(equality_col_idx, dtype, literal, stream, mr);
+        return query_bloom_filter<T>(equality_col_idx, dtype, literal, stream, mr);
       }
     } else {
-      return compute_column<T>(equality_col_idx, dtype, literal, stream, mr);
+      return query_bloom_filter<T>(equality_col_idx, dtype, literal, stream, mr);
     }
   }
 };

From 9a39aa4be813370275ee320c21fd68116ed22b56 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 27 Nov 2024 01:25:34 +0000
Subject: [PATCH 37/82] Minor improvements

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 11 +++++------
 1 file changed, 5 insertions(+), 6 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index df6d48618b0..14fda5911e8 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -271,10 +271,9 @@ class equality_literals_collector : public ast::detail::expression_transformer {
  */
 class bloom_filter_expression_converter : public equality_literals_collector {
  public:
-  bloom_filter_expression_converter(
-    ast::expression const& expr,
-    size_type num_input_columns,
-    std::vector<std::vector<ast::literal*>> const& equality_literals)
+  bloom_filter_expression_converter(ast::expression const& expr,
+                                    size_type num_input_columns,
+                                    std::vector<std::vector<ast::literal*>>& equality_literals)
   {
     // Set the num columns and equality literals
     _num_input_columns = num_input_columns;
@@ -594,7 +593,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
     [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
 
   // Collect equality literals for each input table column
-  auto const equality_literals =
+  auto equality_literals =
     equality_literals_collector{filter.get(), num_input_columns}.get_equality_literals();
 
   // Collect schema indices of columns with equality predicate(s)
@@ -613,7 +612,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Read a vector of bloom filter bitset device buffers for all column with equality
   // predicate(s) across all row groups
-  auto bloom_filter_data =
+  auto const bloom_filter_data =
     read_bloom_filters(sources, row_group_indices, equality_col_schemas, num_row_groups, stream);
 
   // No bloom filter buffers, return the original row group indices

From 1def80102140e02d325a09b03eb866b1bfb9e0b5 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 27 Nov 2024 01:34:14 +0000
Subject: [PATCH 38/82] Fix minor bug

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 14fda5911e8..f044b49e55f 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -271,13 +271,14 @@ class equality_literals_collector : public ast::detail::expression_transformer {
  */
 class bloom_filter_expression_converter : public equality_literals_collector {
  public:
-  bloom_filter_expression_converter(ast::expression const& expr,
-                                    size_type num_input_columns,
-                                    std::vector<std::vector<ast::literal*>>& equality_literals)
+  bloom_filter_expression_converter(
+    ast::expression const& expr,
+    size_type num_input_columns,
+    std::vector<std::vector<ast::literal*>> const& equality_literals)
   {
-    // Set the num columns and equality literals
+    // Set the num columns and copy equality literals
     _num_input_columns = num_input_columns;
-    _equality_literals = std::move(equality_literals);
+    _equality_literals = equality_literals;
 
     // Compute and store columns literals offsets
     _col_literals_offsets.reserve(_num_input_columns + 1);
@@ -593,7 +594,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
     [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
 
   // Collect equality literals for each input table column
-  auto equality_literals =
+  auto const equality_literals =
     equality_literals_collector{filter.get(), num_input_columns}.get_equality_literals();
 
   // Collect schema indices of columns with equality predicate(s)

From 6edc2481447d2170a28a6d1b4645a907d0909e7d Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 28 Nov 2024 01:00:06 +0000
Subject: [PATCH 39/82] MInor bug fixing

---
 cpp/src/io/parquet/bloom_filter_reader.cu  | 14 +++++++-------
 cpp/src/io/parquet/predicate_pushdown.cpp  |  4 ++--
 cpp/src/io/parquet/reader_impl_helpers.hpp |  4 ++--
 3 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index f044b49e55f..8514ec05cdb 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -575,7 +575,7 @@ std::vector<Type> aggregate_reader_metadata::get_parquet_types(
 
 std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::apply_bloom_filters(
   host_span<std::unique_ptr<datasource> const> sources,
-  host_span<std::vector<size_type> const> row_group_indices,
+  host_span<std::vector<size_type> const> input_row_group_indices,
   host_span<data_type const> output_dtypes,
   host_span<int const> output_column_schemas,
   std::reference_wrapper<ast::expression const> filter,
@@ -588,8 +588,8 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Total number of row groups to process.
   auto const num_row_groups = std::accumulate(
-    row_group_indices.begin(),
-    row_group_indices.end(),
+    input_row_group_indices.begin(),
+    input_row_group_indices.end(),
     size_t{0},
     [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
 
@@ -613,14 +613,14 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Read a vector of bloom filter bitset device buffers for all column with equality
   // predicate(s) across all row groups
-  auto const bloom_filter_data =
-    read_bloom_filters(sources, row_group_indices, equality_col_schemas, num_row_groups, stream);
+  auto const bloom_filter_data = read_bloom_filters(
+    sources, input_row_group_indices, equality_col_schemas, num_row_groups, stream);
 
   // No bloom filter buffers, return the original row group indices
   if (bloom_filter_data.empty()) { return std::nullopt; }
 
   // Get parquet types for the predicate columns
-  auto const parquet_types = get_parquet_types(row_group_indices, equality_col_schemas);
+  auto const parquet_types = get_parquet_types(input_row_group_indices, equality_col_schemas);
 
   // Copy bloom filter bitset buffer pointers and sizes to device
   std::vector<void*> h_buffer_ptrs(bloom_filter_data.size());
@@ -674,7 +674,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   // filtered row group indices
   return collect_filtered_row_group_indices(bloom_filter_membership_table,
                                             bloom_filter_expr.get_bloom_filter_expr(),
-                                            row_group_indices,
+                                            input_row_group_indices,
                                             stream,
                                             mr);
 }
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index ba6f690abd3..65ea51f50f3 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -450,8 +450,8 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
   stats_expression_converter stats_expr{filter.get(), static_cast<size_type>(output_dtypes.size())};
 
   // Filter stats table with StatsAST expression and collect filtered row group indices
-  auto filtered_row_group_indices = collect_filtered_row_group_indices(
-    stats_table, stats_expr.get_stats_expr(), row_group_indices, stream, mr);
+  auto const filtered_row_group_indices = collect_filtered_row_group_indices(
+    stats_table, stats_expr.get_stats_expr(), input_row_group_indices, stream, mr);
 
   // Span on row groups to apply bloom filtering on.
   auto const bloom_filter_input_row_groups =
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index c280341ead7..9cc2e0e8be8 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -375,7 +375,7 @@ class aggregate_reader_metadata {
    * @brief Filters the row groups using bloom filters
    *
    * @param sources Dataset sources
-   * @param row_group_indices Lists of row groups to read, one per source
+   * @param row_group_indices Lists of input row groups to read, one per source
    * @param output_dtypes Datatypes of of output columns
    * @param output_column_schemas schema indices of output columns
    * @param filter AST expression to filter row groups based on bloom filter membership
@@ -385,7 +385,7 @@ class aggregate_reader_metadata {
    */
   [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> apply_bloom_filters(
     host_span<std::unique_ptr<datasource> const> sources,
-    host_span<std::vector<size_type> const> row_group_indices,
+    host_span<std::vector<size_type> const> input_row_group_indices,
     host_span<data_type const> output_dtypes,
     host_span<int const> output_column_schemas,
     std::reference_wrapper<ast::expression const> filter,

From 2925f1e0098ba57ac79e8f4dfab53c7265bc8100 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 28 Nov 2024 02:19:42 +0000
Subject: [PATCH 40/82] Add python tests

---
 ...d_ndv_100_bf_fpp0.1_nostats.snappy.parquet | Bin 0 -> 14057 bytes
 ...ed_card_ndv_100_chunk_stats.snappy.parquet | Bin 0 -> 12413 bytes
 ...d_ndv_500_bf_fpp0.1_nostats.snappy.parquet | Bin 0 -> 37510 bytes
 ...ed_card_ndv_500_chunk_stats.snappy.parquet | Bin 0 -> 33028 bytes
 python/cudf/cudf/tests/test_parquet.py        |  54 ++++++++++++++++++
 5 files changed, 54 insertions(+)
 create mode 100644 python/cudf/cudf/tests/data/parquet/mixed_card_ndv_100_bf_fpp0.1_nostats.snappy.parquet
 create mode 100644 python/cudf/cudf/tests/data/parquet/mixed_card_ndv_100_chunk_stats.snappy.parquet
 create mode 100644 python/cudf/cudf/tests/data/parquet/mixed_card_ndv_500_bf_fpp0.1_nostats.snappy.parquet
 create mode 100644 python/cudf/cudf/tests/data/parquet/mixed_card_ndv_500_chunk_stats.snappy.parquet

diff --git a/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_100_bf_fpp0.1_nostats.snappy.parquet b/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_100_bf_fpp0.1_nostats.snappy.parquet
new file mode 100644
index 0000000000000000000000000000000000000000..8c40a225c44f946689afcb71c495fcadaf195a22
GIT binary patch
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new file mode 100644
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Do`x(*

literal 0
HcmV?d00001

diff --git a/python/cudf/cudf/tests/test_parquet.py b/python/cudf/cudf/tests/test_parquet.py
index 659d2ebd89a..6ba0f78d434 100644
--- a/python/cudf/cudf/tests/test_parquet.py
+++ b/python/cudf/cudf/tests/test_parquet.py
@@ -1,6 +1,7 @@
 # Copyright (c) 2019-2024, NVIDIA CORPORATION.
 
 import datetime
+import decimal
 import glob
 import hashlib
 import math
@@ -4341,3 +4342,56 @@ def test_parquet_reader_mismatched_nullability_structs(tmpdir):
         cudf.read_parquet([buf2, buf1]),
         cudf.concat([df2, df1]).reset_index(drop=True),
     )
+
+
+@pytest.mark.parametrize(
+    "stats_fname,bloom_filter_fname",
+    [
+        (
+            "mixed_card_ndv_100_chunk_stats.snappy.parquet",
+            "mixed_card_ndv_100_bf_fpp0.1_nostats.snappy.parquet",
+        ),
+        (
+            "mixed_card_ndv_500_chunk_stats.snappy.parquet",
+            "mixed_card_ndv_500_bf_fpp0.1_nostats.snappy.parquet",
+        ),
+    ],
+)
+@pytest.mark.parametrize(
+    "predicate,expected_len",
+    [
+        ([[("str", "==", "FINDME")], [("fp64", "==", float(500))]], 2),
+        ([("fixed_pt", "==", decimal.Decimal(float(500)))], 2),
+        ([[("ui32", "==", np.uint32(500)), ("str", "==", "FINDME")]], 2),
+        (
+            [
+                ("str", "!=", "FINDME"),
+                ("fixed_pt", "==", decimal.Decimal(float(500))),
+            ],
+            0,
+        ),
+    ],
+)
+def test_parquet_bloom_filters(
+    datadir, stats_fname, bloom_filter_fname, predicate, expected_len
+):
+    fname_stats = datadir / stats_fname
+    fname_bf = datadir / bloom_filter_fname
+    df_stats = cudf.read_parquet(fname_stats, filters=predicate).reset_index(
+        drop=True
+    )
+    df_bf = cudf.read_parquet(fname_bf, filters=predicate).reset_index(
+        drop=True
+    )
+
+    # Check if tables equal
+    assert_eq(
+        df_stats,
+        df_bf,
+    )
+
+    # Check for table length
+    assert_eq(
+        len(df_stats),
+        expected_len,
+    )

From efc6ec0a5c4b956ba86d97259aff6f31b5443401 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 28 Nov 2024 02:28:03 +0000
Subject: [PATCH 41/82] Correct parquet files

---
 ...d_ndv_100_bf_fpp0.1_nostats.snappy.parquet | Bin 14057 -> 41508 bytes
 ...d_ndv_500_bf_fpp0.1_nostats.snappy.parquet | Bin 37510 -> 77985 bytes
 2 files changed, 0 insertions(+), 0 deletions(-)

diff --git a/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_100_bf_fpp0.1_nostats.snappy.parquet b/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_100_bf_fpp0.1_nostats.snappy.parquet
index 8c40a225c44f946689afcb71c495fcadaf195a22..4123545a6e030b7c0b1b7852571348ed53074f72 100644
GIT binary patch
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C`Z6d0

delta 5435
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B*4Y36

diff --git a/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_500_bf_fpp0.1_nostats.snappy.parquet b/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_500_bf_fpp0.1_nostats.snappy.parquet
index 2565b962b0ba920879466b07bdd3b3507be7579b..e898f1d7d1bf6976b661b87b7ea39b615f318102 100644
GIT binary patch
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From a2fa7842c08c619e864934961be1d02e1b7651a7 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Mon, 2 Dec 2024 19:13:09 +0000
Subject: [PATCH 42/82] minor spelling fix

---
 cpp/src/io/parquet/reader_impl_helpers.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 9cc2e0e8be8..f1d55bef326 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -221,7 +221,7 @@ class aggregate_reader_metadata {
    * @param row_group_indices Lists of row groups, once per source
    * @param column_schemas Schema indices of columns whose types will be collected
    *
-   * @return A list of parquet types for the columns matching the procided schema indices
+   * @return A list of parquet types for the columns matching the provided schema indices
    */
   [[nodiscard]] std::vector<Type> get_parquet_types(
     host_span<std::vector<size_type> const> row_group_indices,

From fa0cec85d543c24ff005e9f2dacbda7282c92170 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <14217455+mhaseeb123@users.noreply.github.com>
Date: Mon, 2 Dec 2024 14:09:56 -0800
Subject: [PATCH 43/82] Apply suggestions from code review

Co-authored-by: Bradley Dice <bdice@bradleydice.com>
---
 cpp/src/io/parquet/reader_impl_helpers.hpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index f1d55bef326..7e9881e8947 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -355,7 +355,7 @@ class aggregate_reader_metadata {
   /**
    * @brief Filters the row groups based on predicate filter
    *
-   * @param sources Lists of input datasources.
+   * @param sources Lists of input datasources
    * @param row_group_indices Lists of row groups to read, one per source
    * @param output_dtypes Datatypes of of output columns
    * @param output_column_schemas schema indices of output columns
@@ -397,7 +397,7 @@ class aggregate_reader_metadata {
    * The input `row_start` and `row_count` parameters will be recomputed and output as the valid
    * values based on the input row group list.
    *
-   * @param sources Lists of input datasources.
+   * @param sources Lists of input datasources
    * @param row_group_indices Lists of row groups to read, one per source
    * @param row_start Starting row of the selection
    * @param row_count Total number of rows selected

From 7a309c691bb9c4ddf33451265231c5a2ab7d57c6 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <14217455+mhaseeb123@users.noreply.github.com>
Date: Mon, 2 Dec 2024 22:11:11 +0000
Subject: [PATCH 44/82] Minor bug fix

---
 cpp/include/cudf/hashing/detail/xxhash_64.cuh |  3 ++-
 cpp/src/io/parquet/bloom_filter_reader.cu     | 16 ++++++++--------
 cpp/src/io/parquet/reader_impl_helpers.hpp    | 10 +++++-----
 3 files changed, 15 insertions(+), 14 deletions(-)

diff --git a/cpp/include/cudf/hashing/detail/xxhash_64.cuh b/cpp/include/cudf/hashing/detail/xxhash_64.cuh
index 7d72349e340..53b3fbad842 100644
--- a/cpp/include/cudf/hashing/detail/xxhash_64.cuh
+++ b/cpp/include/cudf/hashing/detail/xxhash_64.cuh
@@ -29,7 +29,8 @@ namespace cudf::hashing::detail {
 
 template <typename Key>
 struct XXHash_64 {
-  using result_type = std::uint64_t;
+  using argument_type = Key;
+  using result_type   = std::uint64_t;
 
   __host__ __device__ constexpr XXHash_64(uint64_t seed = cudf::DEFAULT_HASH_SEED) : _impl{seed} {}
 
diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 8514ec05cdb..dcbf17003d0 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -59,7 +59,7 @@ struct bloom_filter_caster {
   template <typename T, bool timestamp_is_int96 = false>
   std::unique_ptr<cudf::column> query_bloom_filter(cudf::size_type equality_col_idx,
                                                    cudf::data_type dtype,
-                                                   ast::literal* const& literal,
+                                                   ast::literal const* const literal,
                                                    rmm::cuda_stream_view stream,
                                                    rmm::device_async_resource_ref mr) const
   {
@@ -135,7 +135,7 @@ struct bloom_filter_caster {
   template <typename T>
   std::unique_ptr<cudf::column> operator()(cudf::size_type equality_col_idx,
                                            cudf::data_type dtype,
-                                           ast::literal* const& literal,
+                                           ast::literal* const literal,
                                            rmm::cuda_stream_view stream,
                                            rmm::device_async_resource_ref mr) const
   {
@@ -215,15 +215,15 @@ class equality_literals_collector : public ast::detail::expression_transformer {
       // First operand should be column reference, second should be literal.
       CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
                    "Only binary operations are supported on column reference");
-      CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
+      auto const literal_ptr = dynamic_cast<ast::literal const*>(&operands[1].get());
+      CUDF_EXPECTS(literal_ptr != nullptr,
                    "Second operand of binary operation with column reference must be a literal");
       v->accept(*this);
 
       // Push to the corresponding column's literals list iff equality predicate is seen
       if (op == ast_operator::EQUAL) {
         auto const col_idx = v->get_column_index();
-        _equality_literals[col_idx].emplace_back(
-          const_cast<ast::literal*>(dynamic_cast<ast::literal const*>(&operands[1].get())));
+        _equality_literals[col_idx].emplace_back(const_cast<ast::literal*>(literal_ptr));
       }
     } else {
       auto new_operands = visit_operands(operands);
@@ -266,7 +266,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
 };
 
 /**
- * @brief Converts AST expression to bloom filter membership (BloomfilterAST) expression .
+ * @brief Converts AST expression to bloom filter membership (BloomfilterAST) expression.
  * This is used in row group filtering based on equality predicate.
  */
 class bloom_filter_expression_converter : public equality_literals_collector {
@@ -368,7 +368,7 @@ class bloom_filter_expression_converter : public equality_literals_collector {
  *
  * @param sources Dataset sources
  * @param num_chunks Number of total column chunks to read
- * @param bloom_filter_data Devicebuffers to hold bloom filter bitsets for each chunk
+ * @param bloom_filter_data Device buffers to hold bloom filter bitsets for each chunk
  * @param bloom_filter_offsets Bloom filter offsets for all chunks
  * @param bloom_filter_sizes Bloom filter sizes for all chunks
  * @param chunk_source_map Association between each column chunk and its source
@@ -657,7 +657,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
                   if (cudf::is_compound(dtype) and dtype.id() != cudf::type_id::STRING) { return; }
 
                   // Add a column for all literals associated with an equality column
-                  for (ast::literal* const& literal : equality_literals[input_col_idx]) {
+                  for (auto const& literal : equality_literals[input_col_idx]) {
                     columns.emplace_back(cudf::type_dispatcher<dispatch_storage_type>(
                       dtype, bloom_filter_col, equality_col_idx, dtype, literal, stream, mr));
                   }
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 7e9881e8947..2e3e6c6b6dd 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -361,7 +361,7 @@ class aggregate_reader_metadata {
    * @param output_column_schemas schema indices of output columns
    * @param filter AST expression to filter row groups based on Column chunk statistics
    * @param stream CUDA stream used for device memory operations and kernel launches
-   * @return Filtered row group indices, if any is filtered.
+   * @return Filtered row group indices, if any is filtered
    */
   [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> filter_row_groups(
     host_span<std::unique_ptr<datasource> const> sources,
@@ -381,7 +381,7 @@ class aggregate_reader_metadata {
    * @param filter AST expression to filter row groups based on bloom filter membership
    * @param stream CUDA stream used for device memory operations and kernel launches
    *
-   * @return Filtered row group indices, if any is filtered.
+   * @return Filtered row group indices, if any is filtered
    */
   [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> apply_bloom_filters(
     host_span<std::unique_ptr<datasource> const> sources,
@@ -406,7 +406,7 @@ class aggregate_reader_metadata {
    * @param filter Optional AST expression to filter row groups based on Column chunk statistics
    * @param stream CUDA stream used for device memory operations and kernel launches
    * @return A tuple of corrected row_start, row_count, list of row group indexes and its
-   *         starting row, and list of number of rows per source.
+   *         starting row, and list of number of rows per source
    */
   [[nodiscard]] std::tuple<int64_t, size_type, std::vector<row_group_info>, std::vector<size_t>>
   select_row_groups(host_span<std::unique_ptr<datasource> const> sources,
@@ -469,7 +469,7 @@ class named_to_reference_converter : public ast::detail::expression_transformer
   std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override;
 
   /**
-   * @brief Returns the AST to apply on Column chunk statistics.
+   * @brief Returns the AST to apply on Column chunk statistics
    *
    * @return AST operation expression
    */
@@ -506,7 +506,7 @@ class named_to_reference_converter : public ast::detail::expression_transformer
  * collect filtered row group indices
  *
  * @param table Table of stats or bloom filter membership columns
- * @param ast_expr StatsAST or BloomfilterAST expression to filter with.
+ * @param ast_expr StatsAST or BloomfilterAST expression to filter with
  * @param input_row_group_indices Lists of input row groups to read, one per source
  * @param stream CUDA stream used for device memory operations and kernel launches
  * @param mr Device memory resource used to be used in cudf::compute_column

From bcc68c0e896fe59973e74fc6bfe78d24a54d5767 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Mon, 2 Dec 2024 23:26:19 +0000
Subject: [PATCH 45/82] Convert to enum class

---
 cpp/src/io/parquet/parquet.hpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/cpp/src/io/parquet/parquet.hpp b/cpp/src/io/parquet/parquet.hpp
index ff8e7a63486..241f6efbae3 100644
--- a/cpp/src/io/parquet/parquet.hpp
+++ b/cpp/src/io/parquet/parquet.hpp
@@ -400,7 +400,7 @@ struct ColumnChunkMetaData {
  */
 struct BloomFilterAlgorithm {
   // Block-based Bloom filter.
-  enum Algorithm { UNDEFINED, SPLIT_BLOCK };
+  enum class Algorithm { UNDEFINED, SPLIT_BLOCK };
   Algorithm algorithm{Algorithm::SPLIT_BLOCK};
 };
 
@@ -409,7 +409,7 @@ struct BloomFilterAlgorithm {
  */
 struct BloomFilterHash {
   // xxHash_64
-  enum Hash { UNDEFINED, XXHASH };
+  enum class Hash { UNDEFINED, XXHASH };
   Hash hash{Hash::XXHASH};
 };
 
@@ -417,7 +417,7 @@ struct BloomFilterHash {
  * @brief The compression used in the bloom filter
  */
 struct BloomFilterCompression {
-  enum Compression { UNDEFINED, UNCOMPRESSED };
+  enum class Compression { UNDEFINED, UNCOMPRESSED };
   Compression compression{Compression::UNCOMPRESSED};
 };
 

From 2dce9b1589b0bd046bb89262b0d97801bb6f51aa Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 3 Dec 2024 00:38:33 +0000
Subject: [PATCH 46/82] Apply suggestion from code review

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index dcbf17003d0..e42f3dd4111 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -29,6 +29,7 @@
 #include <cudf/hashing/detail/xxhash_64.cuh>
 #include <cudf/utilities/span.hpp>
 #include <cudf/utilities/traits.hpp>
+#include <cudf/utilities/type_checks.hpp>
 
 #include <rmm/cuda_stream_view.hpp>
 #include <rmm/device_buffer.hpp>
@@ -68,9 +69,11 @@ struct bloom_filter_caster {
     using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
     using word_type   = typename policy_type::word_type;
 
-    // Check if the literal has the same type as the column
-    CUDF_EXPECTS(dtype.id() == literal->get_data_type().id(),
-                 "Mismatched data types between the column and the literal");
+    // Check if the literal has the same type as the predicate column
+    CUDF_EXPECTS(
+      cudf::have_same_types(cudf::column_view{dtype, 0, {}, {}, 0, 0, {}},
+                            cudf::column_view{literal->get_data_type(), 0, {}, {}, 0, 0, {}}),
+      "Mismatched predicate column and literal types");
 
     // Filter properties
     auto constexpr word_size       = sizeof(word_type);

From e03bea02c97e060d082b95f934662f387a7aa645 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 3 Dec 2024 20:58:07 +0000
Subject: [PATCH 47/82] Suggestions from code reviews

---
 cpp/src/io/parquet/bloom_filter_reader.cu |  7 ++++++-
 cpp/src/io/parquet/predicate_pushdown.cpp | 19 ++++++++++++-------
 2 files changed, 18 insertions(+), 8 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index e42f3dd4111..7901776c7f6 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -40,6 +40,7 @@
 #include <thrust/iterator/counting_iterator.h>
 
 #include <future>
+#include <limits>
 #include <numeric>
 #include <optional>
 
@@ -476,7 +477,7 @@ std::future<void> read_bloom_filter_data_async(
     }
   };
 
-  return std::async(std::launch::deferred, sync_fn, std::move(read_tasks));
+  return std::async(std::launch::async, sync_fn, std::move(read_tasks));
 }
 
 }  // namespace
@@ -596,6 +597,10 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
     size_t{0},
     [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
 
+  // Check if we have less than 2B total row groups.
+  CUDF_EXPECTS(num_row_groups <= std::numeric_limits<cudf::size_type>::max(),
+               "Total number of row groups exceed the size_type's limit");
+
   // Collect equality literals for each input table column
   auto const equality_literals =
     equality_literals_collector{filter.get(), num_input_columns}.get_equality_literals();
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index 65ea51f50f3..b917c83d524 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -32,6 +32,7 @@
 #include <thrust/iterator/counting_iterator.h>
 
 #include <algorithm>
+#include <limits>
 #include <numeric>
 #include <optional>
 #include <unordered_set>
@@ -415,18 +416,22 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
   } else {
     input_row_group_indices = row_group_indices;
   }
-  auto const total_row_groups = std::accumulate(input_row_group_indices.begin(),
-                                                input_row_group_indices.end(),
-                                                0,
-                                                [](size_type sum, auto const& per_file_row_groups) {
-                                                  return sum + per_file_row_groups.size();
-                                                });
+  auto const total_row_groups = std::accumulate(
+    input_row_group_indices.begin(),
+    input_row_group_indices.end(),
+    size_t{0},
+    [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
+
+  // Check if we have less than 2B total row groups.
+  CUDF_EXPECTS(total_row_groups <= std::numeric_limits<cudf::size_type>::max(),
+               "Total number of row groups exceed the size_type's limit");
 
   // Converts Column chunk statistics to a table
   // where min(col[i]) = columns[i*2], max(col[i])=columns[i*2+1]
   // For each column, it contains #sources * #column_chunks_per_src rows.
   std::vector<std::unique_ptr<column>> columns;
-  stats_caster stats_col{total_row_groups, per_file_metadata, input_row_group_indices};
+  stats_caster stats_col{
+    static_cast<size_type>(total_row_groups), per_file_metadata, input_row_group_indices};
   for (size_t col_idx = 0; col_idx < output_dtypes.size(); col_idx++) {
     auto const schema_idx = output_column_schemas[col_idx];
     auto const& dtype     = output_dtypes[col_idx];

From 4b0b5edb729936490ba74abd57dca5a7ee58bd2f Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 00:31:09 +0000
Subject: [PATCH 48/82] Apply suggestions from code reviews

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 50 ++++++++++++-----------
 1 file changed, 26 insertions(+), 24 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 7901776c7f6..fb2b452fe1a 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -52,8 +52,7 @@ namespace {
  *
  */
 struct bloom_filter_caster {
-  cudf::device_span<void* const> buffer_ptrs;
-  cudf::device_span<size_t const> buffer_sizes;
+  cudf::device_span<cudf::device_span<cuda::std::byte> const> bloom_filter_spans;
   host_span<Type const> parquet_types;
   size_t num_row_groups;
   size_t num_equality_columns;
@@ -87,34 +86,35 @@ struct bloom_filter_caster {
       rmm::exec_policy_nosync(stream),
       thrust::make_counting_iterator<size_t>(0),
       thrust::make_counting_iterator(num_row_groups),
-      [buffer_ptrs          = buffer_ptrs.data(),
-       buffer_sizes         = buffer_sizes.data(),
+      [filter_span          = bloom_filter_spans.data(),
        d_scalar             = literal->get_value(),
        col_idx              = equality_col_idx,
        num_equality_columns = num_equality_columns,
        results = reinterpret_cast<bool*>(results.data())] __device__(auto row_group_idx) {
         // Filter bitset buffer index
-        auto const filter_idx = col_idx + (num_equality_columns * row_group_idx);
+        auto const filter_idx  = col_idx + (num_equality_columns * row_group_idx);
+        auto const filter_size = filter_span[filter_idx].size();
 
         // If no bloom filter, then fill in `true` as membership cannot be determined
-        if (buffer_sizes[filter_idx] == 0) {
+        if (filter_size == 0) {
           results[row_group_idx] = true;
           return;
         }
 
         // Number of filter blocks
-        auto const num_filter_blocks = buffer_sizes[filter_idx] / (word_size * words_per_block);
+        auto const num_filter_blocks = filter_size / (word_size * words_per_block);
 
         // Create a bloom filter view.
         cuco::bloom_filter_ref<key_type,
                                cuco::extent<std::size_t>,
                                cuco::thread_scope_thread,
                                policy_type>
-          filter{reinterpret_cast<word_type*>(buffer_ptrs[filter_idx]),
+          filter{reinterpret_cast<word_type*>(filter_span[filter_idx].data()),
                  num_filter_blocks,
                  {},  // Thread scope as the same literal is being searched across different bitsets
                       // per thread
-                 {}};  // Arrow policy with cudf::XXHash_64 seeded with 0 for Arrow compatibility
+                 {}};  // Arrow policy with cudf::hashing::detail::XXHash_64 seeded with 0 for Arrow
+                       // compatibility
 
         // If int96_timestamp type, convert literal to string_view and query bloom
         // filter
@@ -621,7 +621,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Read a vector of bloom filter bitset device buffers for all column with equality
   // predicate(s) across all row groups
-  auto const bloom_filter_data = read_bloom_filters(
+  auto bloom_filter_data = read_bloom_filters(
     sources, input_row_group_indices, equality_col_schemas, num_row_groups, stream);
 
   // No bloom filter buffers, return the original row group indices
@@ -630,23 +630,25 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   // Get parquet types for the predicate columns
   auto const parquet_types = get_parquet_types(input_row_group_indices, equality_col_schemas);
 
-  // Copy bloom filter bitset buffer pointers and sizes to device
-  std::vector<void*> h_buffer_ptrs(bloom_filter_data.size());
-  std::vector<size_t> h_buffer_sizes(bloom_filter_data.size());
-  std::for_each(thrust::make_counting_iterator<size_t>(0),
-                thrust::make_counting_iterator<size_t>(bloom_filter_data.size()),
-                [&](auto i) {
-                  auto const& buffer = bloom_filter_data[i];
-                  // Bitset ptr must be non-const to be used in cuco::bloom_filter.
-                  h_buffer_ptrs[i]  = const_cast<void*>(buffer.data());
-                  h_buffer_sizes[i] = buffer.size();
-                });
-  auto buffer_ptrs  = cudf::detail::make_device_uvector_async(h_buffer_ptrs, stream, mr);
-  auto buffer_sizes = cudf::detail::make_device_uvector_async(h_buffer_sizes, stream, mr);
+  // Create spans from bloom filter bitset buffers
+  std::vector<cudf::device_span<cuda::std::byte>> h_bloom_filter_spans;
+  h_bloom_filter_spans.reserve(bloom_filter_data.size());
+  std::transform(thrust::make_counting_iterator<size_t>(0),
+                 thrust::make_counting_iterator<size_t>(bloom_filter_data.size()),
+                 std::back_inserter(h_bloom_filter_spans),
+                 [&](auto const filter_idx) {
+                   return cudf::device_span<cuda::std::byte>{
+                     static_cast<cuda::std::byte*>(bloom_filter_data[filter_idx].data()),
+                     bloom_filter_data[filter_idx].size()};
+                 });
+
+  // Copy bloom filter bitset spans to device
+  auto const bloom_filter_spans =
+    cudf::detail::make_device_uvector_async(h_bloom_filter_spans, stream, mr);
 
   // Create a bloom filter query table caster.
   bloom_filter_caster bloom_filter_col{
-    buffer_ptrs, buffer_sizes, parquet_types, num_row_groups, equality_col_schemas.size()};
+    bloom_filter_spans, parquet_types, num_row_groups, equality_col_schemas.size()};
 
   // Converts bloom filter membership for equality predicate columns to a table
   // containing a column for each `col[i] == literal` predicate to be evaluated.

From c1256b135939249f79f90293dbe91e9cce967ece Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 05:01:53 +0000
Subject: [PATCH 49/82] Refactor into single table for cudf::compute_column

---
 cpp/src/io/parquet/bloom_filter_reader.cu     | 242 +++---------
 cpp/src/io/parquet/predicate_pushdown.cpp     | 346 +++++++++---------
 cpp/src/io/parquet/reader_impl_helpers.hpp    |  93 ++++-
 ...ed_card_ndv_100_chunk_stats.snappy.parquet | Bin 12413 -> 37036 bytes
 ...ed_card_ndv_500_chunk_stats.snappy.parquet | Bin 33028 -> 58150 bytes
 5 files changed, 298 insertions(+), 383 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index fb2b452fe1a..5054051b042 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -23,7 +23,6 @@
 #include <cudf/ast/detail/operators.hpp>
 #include <cudf/ast/expressions.hpp>
 #include <cudf/detail/cuco_helpers.hpp>
-#include <cudf/detail/iterator.cuh>
 #include <cudf/detail/transform.hpp>
 #include <cudf/detail/utilities/logger.hpp>
 #include <cudf/hashing/detail/xxhash_64.cuh>
@@ -33,7 +32,6 @@
 
 #include <rmm/cuda_stream_view.hpp>
 #include <rmm/device_buffer.hpp>
-#include <rmm/device_vector.hpp>
 #include <rmm/exec_policy.hpp>
 
 #include <cuco/bloom_filter_ref.cuh>
@@ -54,7 +52,7 @@ namespace {
 struct bloom_filter_caster {
   cudf::device_span<cudf::device_span<cuda::std::byte> const> bloom_filter_spans;
   host_span<Type const> parquet_types;
-  size_t num_row_groups;
+  size_t total_row_groups;
   size_t num_equality_columns;
 
   template <typename T, bool timestamp_is_int96 = false>
@@ -79,13 +77,13 @@ struct bloom_filter_caster {
     auto constexpr word_size       = sizeof(word_type);
     auto constexpr words_per_block = policy_type::words_per_block;
 
-    rmm::device_buffer results{num_row_groups, stream, mr};
+    rmm::device_buffer results{total_row_groups, stream, mr};
 
     // Query literal in bloom filters from each column chunk (row group).
     thrust::for_each(
       rmm::exec_policy_nosync(stream),
       thrust::make_counting_iterator<size_t>(0),
-      thrust::make_counting_iterator(num_row_groups),
+      thrust::make_counting_iterator(total_row_groups),
       [filter_span          = bloom_filter_spans.data(),
        d_scalar             = literal->get_value(),
        col_idx              = equality_col_idx,
@@ -129,7 +127,7 @@ struct bloom_filter_caster {
       });
 
     return std::make_unique<cudf::column>(cudf::data_type{cudf::type_id::BOOL8},
-                                          static_cast<cudf::size_type>(num_row_groups),
+                                          static_cast<cudf::size_type>(total_row_groups),
                                           std::move(results),
                                           rmm::device_buffer{},
                                           0);
@@ -164,47 +162,22 @@ struct bloom_filter_caster {
  * @brief Collects lists of equality predicate literals in the AST expression, one list per input
  * table column. This is used in row group filtering based on bloom filters.
  */
-class equality_literals_collector : public ast::detail::expression_transformer {
+class equality_literals_collector : public combined_expression_converter {
  public:
-  equality_literals_collector() = default;
-
   equality_literals_collector(ast::expression const& expr, cudf::size_type num_input_columns)
-    : _num_input_columns{num_input_columns}
   {
+    _num_input_columns = num_input_columns;
     _equality_literals.resize(_num_input_columns);
     expr.accept(*this);
   }
 
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::literal const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override
-  {
-    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(expr);
-    return expr;
-  }
-
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::column_reference const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override
-  {
-    CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
-                 "BloomfilterAST supports only left table");
-    CUDF_EXPECTS(expr.get_column_index() < _num_input_columns,
-                 "Column index cannot be more than number of columns in the table");
-    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(expr);
-    return expr;
-  }
+  // Bring all overloads of `visit` from combined_expression_converter into scope
+  using combined_expression_converter::visit;
 
   /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::column_name_reference const& )
+   * @brief Delete converted expression getter as no longer needed
    */
-  std::reference_wrapper<ast::expression const> visit(
-    ast::column_name_reference const& expr) override
-  {
-    CUDF_FAIL("Column name reference is not supported in BloomfilterAST");
-  }
+  [[nodiscard]] std::reference_wrapper<ast::expression const> get_converted_expr() = delete;
 
   /**
    * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
@@ -237,7 +210,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
         _operators.emplace_back(op, new_operands.front());
       }
     }
-    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    _converted_expr = std::reference_wrapper<ast::expression const>(_operators.back());
     return std::reference_wrapper<ast::expression const>(_operators.back());
   }
 
@@ -250,121 +223,6 @@ class equality_literals_collector : public ast::detail::expression_transformer {
   {
     return _equality_literals;
   }
-
- protected:
-  std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
-    cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
-  {
-    std::vector<std::reference_wrapper<ast::expression const>> transformed_operands;
-    for (auto const& operand : operands) {
-      auto const new_operand = operand.get().accept(*this);
-      transformed_operands.push_back(new_operand);
-    }
-    return transformed_operands;
-  }
-  std::optional<std::reference_wrapper<ast::expression const>> _bloom_filter_expr;
-  std::vector<std::vector<ast::literal*>> _equality_literals;
-  std::list<ast::column_reference> _col_ref;
-  std::list<ast::operation> _operators;
-  size_type _num_input_columns;
-};
-
-/**
- * @brief Converts AST expression to bloom filter membership (BloomfilterAST) expression.
- * This is used in row group filtering based on equality predicate.
- */
-class bloom_filter_expression_converter : public equality_literals_collector {
- public:
-  bloom_filter_expression_converter(
-    ast::expression const& expr,
-    size_type num_input_columns,
-    std::vector<std::vector<ast::literal*>> const& equality_literals)
-  {
-    // Set the num columns and copy equality literals
-    _num_input_columns = num_input_columns;
-    _equality_literals = equality_literals;
-
-    // Compute and store columns literals offsets
-    _col_literals_offsets.reserve(_num_input_columns + 1);
-    _col_literals_offsets.emplace_back(0);
-
-    std::transform(equality_literals.begin(),
-                   equality_literals.end(),
-                   std::back_inserter(_col_literals_offsets),
-                   [&](auto const& col_literal_map) {
-                     return _col_literals_offsets.back() +
-                            static_cast<cudf::size_type>(col_literal_map.size());
-                   });
-
-    // Add this visitor
-    expr.accept(*this);
-  }
-
-  /**
-   * @brief Delete equality literals getter as no longer needed
-   */
-  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() = delete;
-
-  // Bring all overloads of `visit` from equality_predicate_collector into scope
-  using equality_literals_collector::visit;
-
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override
-  {
-    using cudf::ast::ast_operator;
-    auto const operands = expr.get_operands();
-    auto const op       = expr.get_operator();
-
-    if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
-      // First operand should be column reference, second should be literal.
-      CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
-                   "Only binary operations are supported on column reference");
-      CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
-                   "Second operand of binary operation with column reference must be a literal");
-      v->accept(*this);
-
-      if (op == ast_operator::EQUAL) {
-        // Search the literal in this input column's equality literals list and add to the offset.
-        auto const col_idx            = v->get_column_index();
-        auto const& equality_literals = _equality_literals[col_idx];
-        auto col_literal_offset       = _col_literals_offsets[col_idx];
-        auto const literal_iter       = std::find(equality_literals.cbegin(),
-                                            equality_literals.cend(),
-                                            dynamic_cast<ast::literal const*>(&operands[1].get()));
-        CUDF_EXPECTS(literal_iter != equality_literals.end(), "Could not find the literal ptr");
-        col_literal_offset += std::distance(equality_literals.cbegin(), literal_iter);
-
-        // Evaluate boolean is_true(value) expression as NOT(NOT(value))
-        auto const& value = _col_ref.emplace_back(col_literal_offset);
-        auto const& op    = _operators.emplace_back(ast_operator::NOT, value);
-        _operators.emplace_back(ast_operator::NOT, op);
-      }
-    } else {
-      auto new_operands = visit_operands(operands);
-      if (cudf::ast::detail::ast_operator_arity(op) == 2) {
-        _operators.emplace_back(op, new_operands.front(), new_operands.back());
-      } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
-        _operators.emplace_back(op, new_operands.front());
-      }
-    }
-    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(_operators.back());
-    return std::reference_wrapper<ast::expression const>(_operators.back());
-  }
-
-  /**
-   * @brief Returns the AST to apply on bloom filters mmebership.
-   *
-   * @return AST operation expression
-   */
-  [[nodiscard]] std::reference_wrapper<ast::expression const> get_bloom_filter_expr() const
-  {
-    return _bloom_filter_expr.value().get();
-  }
-
- private:
-  std::vector<cudf::size_type> _col_literals_offsets;
 };
 
 /**
@@ -486,12 +344,12 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> row_group_indices,
   host_span<int const> column_schemas,
-  size_type num_row_groups,
+  size_type total_row_groups,
   rmm::cuda_stream_view stream) const
 {
   // Descriptors for all the chunks that make up the selected columns
   auto const num_input_columns = column_schemas.size();
-  auto const num_chunks        = num_row_groups * num_input_columns;
+  auto const num_chunks        = total_row_groups * num_input_columns;
 
   // Association between each column chunk and its source
   std::vector<size_type> chunk_source_map(num_chunks);
@@ -577,12 +435,14 @@ std::vector<Type> aggregate_reader_metadata::get_parquet_types(
   return parquet_types;
 }
 
-std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::apply_bloom_filters(
+std::pair<std::vector<std::unique_ptr<cudf::column>>, std::vector<std::vector<ast::literal*>>>
+aggregate_reader_metadata::apply_bloom_filters(
   host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> input_row_group_indices,
   host_span<data_type const> output_dtypes,
   host_span<int const> output_column_schemas,
   std::reference_wrapper<ast::expression const> filter,
+  size_t total_row_groups,
   rmm::cuda_stream_view stream) const
 {
   // Number of input table columns
@@ -590,17 +450,6 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   auto mr = cudf::get_current_device_resource_ref();
 
-  // Total number of row groups to process.
-  auto const num_row_groups = std::accumulate(
-    input_row_group_indices.begin(),
-    input_row_group_indices.end(),
-    size_t{0},
-    [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
-
-  // Check if we have less than 2B total row groups.
-  CUDF_EXPECTS(num_row_groups <= std::numeric_limits<cudf::size_type>::max(),
-               "Total number of row groups exceed the size_type's limit");
-
   // Collect equality literals for each input table column
   auto const equality_literals =
     equality_literals_collector{filter.get(), num_input_columns}.get_equality_literals();
@@ -616,16 +465,19 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
                   }
                 });
 
+  // Read bloom filters and add literal membership columns.
+  std::vector<std::unique_ptr<cudf::column>> bloom_filter_membership_columns;
+
   // Return early if no column with equality predicate(s)
-  if (equality_col_schemas.empty()) { return std::nullopt; }
+  if (equality_col_schemas.empty()) { return {}; }
 
   // Read a vector of bloom filter bitset device buffers for all column with equality
   // predicate(s) across all row groups
   auto bloom_filter_data = read_bloom_filters(
-    sources, input_row_group_indices, equality_col_schemas, num_row_groups, stream);
+    sources, input_row_group_indices, equality_col_schemas, total_row_groups, stream);
 
   // No bloom filter buffers, return the original row group indices
-  if (bloom_filter_data.empty()) { return std::nullopt; }
+  if (bloom_filter_data.empty()) { return {}; }
 
   // Get parquet types for the predicate columns
   auto const parquet_types = get_parquet_types(input_row_group_indices, equality_col_schemas);
@@ -648,45 +500,33 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Create a bloom filter query table caster.
   bloom_filter_caster bloom_filter_col{
-    bloom_filter_spans, parquet_types, num_row_groups, equality_col_schemas.size()};
+    bloom_filter_spans, parquet_types, total_row_groups, equality_col_schemas.size()};
 
   // Converts bloom filter membership for equality predicate columns to a table
   // containing a column for each `col[i] == literal` predicate to be evaluated.
   // The table contains #sources * #column_chunks_per_src rows.
-  std::vector<std::unique_ptr<column>> columns;
   size_t equality_col_idx = 0;
-  std::for_each(thrust::make_counting_iterator<size_t>(0),
-                thrust::make_counting_iterator(output_dtypes.size()),
-                [&](auto input_col_idx) {
-                  auto const& dtype = output_dtypes[input_col_idx];
+  std::for_each(
+    thrust::make_counting_iterator<size_t>(0),
+    thrust::make_counting_iterator(output_dtypes.size()),
+    [&](auto input_col_idx) {
+      auto const& dtype = output_dtypes[input_col_idx];
 
-                  // Skip if no equality literals for this column
-                  if (equality_literals[input_col_idx].empty()) { return; }
+      // Skip if no equality literals for this column
+      if (equality_literals[input_col_idx].empty()) { return; }
 
-                  // Skip if non-comparable (compound) type except string
-                  if (cudf::is_compound(dtype) and dtype.id() != cudf::type_id::STRING) { return; }
+      // Skip if non-comparable (compound) type except string
+      if (cudf::is_compound(dtype) and dtype.id() != cudf::type_id::STRING) { return; }
 
-                  // Add a column for all literals associated with an equality column
-                  for (auto const& literal : equality_literals[input_col_idx]) {
-                    columns.emplace_back(cudf::type_dispatcher<dispatch_storage_type>(
-                      dtype, bloom_filter_col, equality_col_idx, dtype, literal, stream, mr));
-                  }
-                  equality_col_idx++;
-                });
-  auto bloom_filter_membership_table = cudf::table(std::move(columns));
-
-  // Convert AST to BloomfilterAST expression with reference to bloom filter membership
-  // in above `bloom_filter_membership_table`
-  bloom_filter_expression_converter bloom_filter_expr{
-    filter.get(), num_input_columns, equality_literals};
-
-  // Filter bloom filter membership table with the BloomfilterAST expression and collect
-  // filtered row group indices
-  return collect_filtered_row_group_indices(bloom_filter_membership_table,
-                                            bloom_filter_expr.get_bloom_filter_expr(),
-                                            input_row_group_indices,
-                                            stream,
-                                            mr);
+      // Add a column for all literals associated with an equality column
+      for (auto const& literal : equality_literals[input_col_idx]) {
+        bloom_filter_membership_columns.emplace_back(cudf::type_dispatcher<dispatch_storage_type>(
+          dtype, bloom_filter_col, equality_col_idx, dtype, literal, stream, mr));
+      }
+      equality_col_idx++;
+    });
+
+  return {std::move(bloom_filter_membership_columns), std::move(equality_literals)};
 }
 
 }  // namespace cudf::io::parquet::detail
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index c2aa012feb5..5ff8645b569 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -246,149 +246,6 @@ struct stats_caster {
   }
 };
 
-/**
- * @brief Converts AST expression to StatsAST for comparing with column statistics
- * This is used in row group filtering based on predicate.
- * statistics min value of a column is referenced by column_index*2
- * statistics max value of a column is referenced by column_index*2+1
- *
- */
-class stats_expression_converter : public ast::detail::expression_transformer {
- public:
-  stats_expression_converter(ast::expression const& expr, size_type const& num_columns)
-    : _num_columns{num_columns}
-  {
-    expr.accept(*this);
-  }
-
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::literal const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override
-  {
-    _stats_expr = std::reference_wrapper<ast::expression const>(expr);
-    return expr;
-  }
-
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::column_reference const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override
-  {
-    CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
-                 "Statistics AST supports only left table");
-    CUDF_EXPECTS(expr.get_column_index() < _num_columns,
-                 "Column index cannot be more than number of columns in the table");
-    _stats_expr = std::reference_wrapper<ast::expression const>(expr);
-    return expr;
-  }
-
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::column_name_reference const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(
-    ast::column_name_reference const& expr) override
-  {
-    CUDF_FAIL("Column name reference is not supported in statistics AST");
-  }
-
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override
-  {
-    using cudf::ast::ast_operator;
-    auto const operands = expr.get_operands();
-    auto const op       = expr.get_operator();
-
-    if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
-      // First operand should be column reference, second should be literal.
-      CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
-                   "Only binary operations are supported on column reference");
-      CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
-                   "Second operand of binary operation with column reference must be a literal");
-      v->accept(*this);
-      auto const col_index = v->get_column_index();
-      switch (op) {
-        /* transform to stats conditions. op(col, literal)
-        col1 == val --> vmin <= val && vmax >= val
-        col1 != val --> !(vmin == val && vmax == val)
-        col1 >  val --> vmax > val
-        col1 <  val --> vmin < val
-        col1 >= val --> vmax >= val
-        col1 <= val --> vmin <= val
-        */
-        case ast_operator::EQUAL: {
-          auto const& vmin = _col_ref.emplace_back(col_index * 2);
-          auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
-          auto const& op1 =
-            _operators.emplace_back(ast_operator::LESS_EQUAL, vmin, operands[1].get());
-          auto const& op2 =
-            _operators.emplace_back(ast_operator::GREATER_EQUAL, vmax, operands[1].get());
-          _operators.emplace_back(ast::ast_operator::LOGICAL_AND, op1, op2);
-          break;
-        }
-        case ast_operator::NOT_EQUAL: {
-          auto const& vmin = _col_ref.emplace_back(col_index * 2);
-          auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
-          auto const& op1  = _operators.emplace_back(ast_operator::NOT_EQUAL, vmin, vmax);
-          auto const& op2 =
-            _operators.emplace_back(ast_operator::NOT_EQUAL, vmax, operands[1].get());
-          _operators.emplace_back(ast_operator::LOGICAL_OR, op1, op2);
-          break;
-        }
-        case ast_operator::LESS: [[fallthrough]];
-        case ast_operator::LESS_EQUAL: {
-          auto const& vmin = _col_ref.emplace_back(col_index * 2);
-          _operators.emplace_back(op, vmin, operands[1].get());
-          break;
-        }
-        case ast_operator::GREATER: [[fallthrough]];
-        case ast_operator::GREATER_EQUAL: {
-          auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
-          _operators.emplace_back(op, vmax, operands[1].get());
-          break;
-        }
-        default: CUDF_FAIL("Unsupported operation in Statistics AST");
-      };
-    } else {
-      auto new_operands = visit_operands(operands);
-      if (cudf::ast::detail::ast_operator_arity(op) == 2) {
-        _operators.emplace_back(op, new_operands.front(), new_operands.back());
-      } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
-        _operators.emplace_back(op, new_operands.front());
-      }
-    }
-    _stats_expr = std::reference_wrapper<ast::expression const>(_operators.back());
-    return std::reference_wrapper<ast::expression const>(_operators.back());
-  }
-
-  /**
-   * @brief Returns the AST to apply on Column chunk statistics.
-   *
-   * @return AST operation expression
-   */
-  [[nodiscard]] std::reference_wrapper<ast::expression const> get_stats_expr() const
-  {
-    return _stats_expr.value().get();
-  }
-
- private:
-  std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
-    cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
-  {
-    std::vector<std::reference_wrapper<ast::expression const>> transformed_operands;
-    for (auto const& operand : operands) {
-      auto const new_operand = operand.get().accept(*this);
-      transformed_operands.push_back(new_operand);
-    }
-    return transformed_operands;
-  }
-  std::optional<std::reference_wrapper<ast::expression const>> _stats_expr;
-  size_type _num_columns;
-  std::list<ast::column_reference> _col_ref;
-  std::list<ast::operation> _operators;
-};
 }  // namespace
 
 std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::filter_row_groups(
@@ -399,6 +256,9 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
   std::reference_wrapper<ast::expression const> filter,
   rmm::cuda_stream_view stream) const
 {
+  // Number of input table columns
+  auto const num_input_columns = static_cast<cudf::size_type>(output_dtypes.size());
+
   auto mr = cudf::get_current_device_resource_ref();
   // Create row group indices.
   std::vector<std::vector<size_type>> all_row_group_indices;
@@ -449,34 +309,180 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
     columns.push_back(std::move(min_col));
     columns.push_back(std::move(max_col));
   }
-  auto stats_table = cudf::table(std::move(columns));
 
-  // Converts AST to StatsAST with reference to min, max columns in above `stats_table`.
-  stats_expression_converter const stats_expr{filter.get(),
-                                              static_cast<size_type>(output_dtypes.size())};
-  auto stats_ast     = stats_expr.get_stats_expr();
-  auto predicate_col = cudf::detail::compute_column(stats_table, stats_ast.get(), stream, mr);
-  auto predicate     = predicate_col->view();
-  CUDF_EXPECTS(predicate.type().id() == cudf::type_id::BOOL8,
-               "Filter expression must return a boolean column");
+  // Apply bloom filter membership to row groups for each equality predicate column, literal pair
+  // and get corresponding boolean columns.
+  auto [bloom_filter_membership_cols, equality_literals] =
+    apply_bloom_filters(sources,
+                        input_row_group_indices,
+                        output_dtypes,
+                        output_column_schemas,
+                        filter,
+                        total_row_groups,
+                        stream);
+
+  // Check if we have any bloom filter membership columns
+  auto const has_bloom_filters = not bloom_filter_membership_cols.empty();
+
+  // Append bloom filter membership columns to stats columns to get combined columns if needed
+  if (has_bloom_filters) {
+    columns.insert(columns.end(),
+                   std::make_move_iterator(bloom_filter_membership_cols.begin()),
+                   std::make_move_iterator(bloom_filter_membership_cols.end()));
+  }
 
-  // Filter stats table with StatsAST expression and collect filtered row group indices
-  auto const filtered_row_group_indices = collect_filtered_row_group_indices(
-    stats_table, stats_expr.get_stats_expr(), input_row_group_indices, stream, mr);
+  auto combined_table = cudf::table(std::move(columns));
 
-  // Span on row groups to apply bloom filtering on.
-  auto const bloom_filter_input_row_groups =
-    filtered_row_group_indices.has_value()
-      ? host_span<std::vector<size_type> const>(filtered_row_group_indices.value())
-      : input_row_group_indices;
+  // Convert AST to a CombinedAST (StatsAST and BloomfilterAST) expression
+  combined_expression_converter combined_expr{
+    filter.get(), num_input_columns, equality_literals, has_bloom_filters};
+
+  // Filter combined table with the AST expression and collect filtered row group indices
+  return collect_filtered_row_group_indices(
+    combined_table, combined_expr.get_converted_expr(), input_row_group_indices, stream, mr);
+}
+
+// Convert AST expression to a CombinedAST (StatsAST and BloomfilterAST)
+combined_expression_converter::combined_expression_converter(
+  ast::expression const& expr,
+  size_type num_input_columns,
+  std::vector<std::vector<ast::literal*>> const& equality_literals,
+  bool has_bloom_filters)
+  : _has_bloom_filters{has_bloom_filters}
+{
+  // Set the num columns and copy equality literals
+  _num_input_columns = num_input_columns;
+  _equality_literals = equality_literals;
+
+  // Compute and store columns literals offsets
+  _col_literals_offsets.reserve(_num_input_columns + 1);
+  _col_literals_offsets.emplace_back(0);
+
+  std::transform(equality_literals.begin(),
+                 equality_literals.end(),
+                 std::back_inserter(_col_literals_offsets),
+                 [&](auto const& col_literal_map) {
+                   return _col_literals_offsets.back() +
+                          static_cast<cudf::size_type>(col_literal_map.size());
+                 });
+
+  // Add this visitor
+  expr.accept(*this);
+}
+
+std::reference_wrapper<ast::expression const> combined_expression_converter::visit(
+  ast::literal const& expr)
+{
+  _converted_expr = std::reference_wrapper<ast::expression const>(expr);
+  return expr;
+}
+
+std::reference_wrapper<ast::expression const> combined_expression_converter::visit(
+  ast::column_reference const& expr)
+{
+  CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
+               "CombinedAST (Stats and Bloomfilter) supports only left table");
+  CUDF_EXPECTS(expr.get_column_index() < _num_input_columns,
+               "Column index cannot be more than number of columns in the table");
+  _converted_expr = std::reference_wrapper<ast::expression const>(expr);
+  return expr;
+}
 
-  // Apply bloom filtering on the bloom filter input row groups
-  auto const bloom_filtered_row_groups = apply_bloom_filters(
-    sources, bloom_filter_input_row_groups, output_dtypes, output_column_schemas, filter, stream);
+std::reference_wrapper<ast::expression const> combined_expression_converter::visit(
+  ast::operation const& expr)
+{
+  using cudf::ast::ast_operator;
+  auto const operands = expr.get_operands();
+  auto const op       = expr.get_operator();
+
+  if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
+    // First operand should be column reference, second should be literal.
+    CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
+                 "Only binary operations are supported on column reference");
+    CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
+                 "Second operand of binary operation with column reference must be a literal");
+    v->accept(*this);
+    auto const col_index = v->get_column_index();
+    switch (op) {
+      /* transform to stats conditions. op(col, literal)
+      col1 == val --> vmin <= val && vmax >= val && bloom_filter[col1, val].contains(val)
+      col1 != val --> !(vmin == val && vmax == val)
+      col1 >  val --> vmax > val
+      col1 <  val --> vmin < val
+      col1 >= val --> vmax >= val
+      col1 <= val --> vmin <= val
+      */
+      case ast_operator::EQUAL: {
+        auto const& vmin = _col_ref.emplace_back(col_index * 2);
+        auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
+        auto const& op1 =
+          _operators.emplace_back(ast_operator::LESS_EQUAL, vmin, operands[1].get());
+        auto const& op2 =
+          _operators.emplace_back(ast_operator::GREATER_EQUAL, vmax, operands[1].get());
+        _operators.emplace_back(ast::ast_operator::LOGICAL_AND, op1, op2);
+
+        // Use this input column's bloom filter membership column as well if available.
+        if (_has_bloom_filters) {
+          auto const& equality_literals = _equality_literals[col_index];
+          auto col_literal_offset = (_num_input_columns * 2) + _col_literals_offsets[col_index];
+          auto const literal_iter =
+            std::find(equality_literals.cbegin(),
+                      equality_literals.cend(),
+                      dynamic_cast<ast::literal const*>(&operands[1].get()));
+          CUDF_EXPECTS(literal_iter != equality_literals.end(), "Could not find the literal ptr");
+          col_literal_offset += std::distance(equality_literals.cbegin(), literal_iter);
+
+          // Evaluate boolean is_true(value) expression as NOT(NOT(value))
+          auto const& value = _col_ref.emplace_back(col_literal_offset);
+          auto const& op    = _operators.emplace_back(ast_operator::NOT, value);
+          _operators.emplace_back(ast_operator::NOT, op);
+        }
+        break;
+      }
+      case ast_operator::NOT_EQUAL: {
+        auto const& vmin = _col_ref.emplace_back(col_index * 2);
+        auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
+        auto const& op1  = _operators.emplace_back(ast_operator::NOT_EQUAL, vmin, vmax);
+        auto const& op2 = _operators.emplace_back(ast_operator::NOT_EQUAL, vmax, operands[1].get());
+        _operators.emplace_back(ast_operator::LOGICAL_OR, op1, op2);
+        break;
+      }
+      case ast_operator::LESS: [[fallthrough]];
+      case ast_operator::LESS_EQUAL: {
+        auto const& vmin = _col_ref.emplace_back(col_index * 2);
+        _operators.emplace_back(op, vmin, operands[1].get());
+        break;
+      }
+      case ast_operator::GREATER: [[fallthrough]];
+      case ast_operator::GREATER_EQUAL: {
+        auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
+        _operators.emplace_back(op, vmax, operands[1].get());
+        break;
+      }
+      default: CUDF_FAIL("Unsupported operation in CombinedAST");
+    };
+  } else {
+    auto new_operands = visit_operands(operands);
+    if (cudf::ast::detail::ast_operator_arity(op) == 2) {
+      _operators.emplace_back(op, new_operands.front(), new_operands.back());
+    } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
+      _operators.emplace_back(op, new_operands.front());
+    }
+  }
+  _converted_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+  return std::reference_wrapper<ast::expression const>(_operators.back());
+}
 
-  // Return bloom filtered row group indices iff collected
-  return bloom_filtered_row_groups.has_value() ? bloom_filtered_row_groups
-                                               : filtered_row_group_indices;
+std::vector<std::reference_wrapper<ast::expression const>>
+combined_expression_converter::visit_operands(
+  cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
+{
+  std::vector<std::reference_wrapper<ast::expression const>> transformed_operands;
+  for (auto const& operand : operands) {
+    auto const new_operand = operand.get().accept(*this);
+    transformed_operands.push_back(new_operand);
+  }
+  return transformed_operands;
 }
 
 // convert column named expression to column index reference expression
@@ -497,14 +503,14 @@ named_to_reference_converter::named_to_reference_converter(
 std::reference_wrapper<ast::expression const> named_to_reference_converter::visit(
   ast::literal const& expr)
 {
-  _stats_expr = std::reference_wrapper<ast::expression const>(expr);
+  _converted_expr = std::reference_wrapper<ast::expression const>(expr);
   return expr;
 }
 
 std::reference_wrapper<ast::expression const> named_to_reference_converter::visit(
   ast::column_reference const& expr)
 {
-  _stats_expr = std::reference_wrapper<ast::expression const>(expr);
+  _converted_expr = std::reference_wrapper<ast::expression const>(expr);
   return expr;
 }
 
@@ -518,7 +524,7 @@ std::reference_wrapper<ast::expression const> named_to_reference_converter::visi
   }
   auto col_index = col_index_it->second;
   _col_ref.emplace_back(col_index);
-  _stats_expr = std::reference_wrapper<ast::expression const>(_col_ref.back());
+  _converted_expr = std::reference_wrapper<ast::expression const>(_col_ref.back());
   return std::reference_wrapper<ast::expression const>(_col_ref.back());
 }
 
@@ -533,7 +539,7 @@ std::reference_wrapper<ast::expression const> named_to_reference_converter::visi
   } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
     _operators.emplace_back(op, new_operands.front());
   }
-  _stats_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+  _converted_expr = std::reference_wrapper<ast::expression const>(_operators.back());
   return std::reference_wrapper<ast::expression const>(_operators.back());
 }
 
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 2e3e6c6b6dd..859d9aadc94 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -372,24 +372,28 @@ class aggregate_reader_metadata {
     rmm::cuda_stream_view stream) const;
 
   /**
-   * @brief Filters the row groups using bloom filters
+   * @brief Computes bloom filter membership for the row groups based on predicate filter
    *
    * @param sources Dataset sources
    * @param row_group_indices Lists of input row groups to read, one per source
    * @param output_dtypes Datatypes of of output columns
    * @param output_column_schemas schema indices of output columns
    * @param filter AST expression to filter row groups based on bloom filter membership
+   * @param total_row_groups Total number of row groups across all input sources.
    * @param stream CUDA stream used for device memory operations and kernel launches
    *
-   * @return Filtered row group indices, if any is filtered
+   * @return A pair of list of bloom filter membership columns and a list of pointers to (equality
+   * predicate) literals associated with each input column.
    */
-  [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> apply_bloom_filters(
-    host_span<std::unique_ptr<datasource> const> sources,
-    host_span<std::vector<size_type> const> input_row_group_indices,
-    host_span<data_type const> output_dtypes,
-    host_span<int const> output_column_schemas,
-    std::reference_wrapper<ast::expression const> filter,
-    rmm::cuda_stream_view stream) const;
+  [[nodiscard]] std::pair<std::vector<std::unique_ptr<cudf::column>>,
+                          std::vector<std::vector<ast::literal*>>>
+  apply_bloom_filters(host_span<std::unique_ptr<datasource> const> sources,
+                      host_span<std::vector<size_type> const> input_row_group_indices,
+                      host_span<data_type const> output_dtypes,
+                      host_span<int const> output_column_schemas,
+                      std::reference_wrapper<ast::expression const> filter,
+                      size_t total_row_groups,
+                      rmm::cuda_stream_view stream) const;
 
   /**
    * @brief Filters and reduces down to a selection of row groups
@@ -441,6 +445,71 @@ class aggregate_reader_metadata {
                  type_id timestamp_type_id);
 };
 
+/**
+ * @brief Converts AST expression to a CombinedAST (StatsAST and BloomfilterAST) for comparing with
+ * column statistics and testing bloom filter membership altogether. This is used in row group
+ * filtering based on predicate.
+ *
+ * statistics min value of a column is referenced by column_index*2
+ * statistics max value of a column is referenced by column_index*2+1
+ * bloom filter membership of each (column, literal) pair is appended to the end of stats.
+ *
+ */
+class combined_expression_converter : public ast::detail::expression_transformer {
+ public:
+  combined_expression_converter() = default;
+  combined_expression_converter(ast::expression const& expr,
+                                size_type num_input_columns,
+                                std::vector<std::vector<ast::literal*>> const& equality_literals,
+                                bool has_bloom_filters);
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::literal const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override;
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override;
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_name_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(
+    ast::column_name_reference const& expr) override
+  {
+    CUDF_FAIL("Column name reference is not supported in CombinedAST");
+  }
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override;
+  /**
+   * @brief Returns the AST to apply Column chunk statistics and bloom filter membership
+   *
+   * @return AST operation expression
+   */
+  [[nodiscard]] std::reference_wrapper<ast::expression const> get_converted_expr() const
+  {
+    return _converted_expr.value().get();
+  }
+
+ protected:
+  std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
+    cudf::host_span<std::reference_wrapper<ast::expression const> const> operands);
+
+  std::optional<std::reference_wrapper<ast::expression const>> _converted_expr;
+  size_type _num_columns;
+  std::list<ast::column_reference> _col_ref;
+  std::list<ast::operation> _operators;
+  std::vector<std::vector<ast::literal*>> _equality_literals;
+  size_type _num_input_columns;
+
+ private:
+  bool _has_bloom_filters;
+  std::vector<cudf::size_type> _col_literals_offsets;
+};
+
 /**
  * @brief Converts named columns to index reference columns
  *
@@ -469,14 +538,14 @@ class named_to_reference_converter : public ast::detail::expression_transformer
   std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override;
 
   /**
-   * @brief Returns the AST to apply on Column chunk statistics
+   * @brief Returns the converted AST expression
    *
    * @return AST operation expression
    */
   [[nodiscard]] std::optional<std::reference_wrapper<ast::expression const>> get_converted_expr()
     const
   {
-    return _stats_expr;
+    return _converted_expr;
   }
 
  private:
@@ -484,7 +553,7 @@ class named_to_reference_converter : public ast::detail::expression_transformer
     cudf::host_span<std::reference_wrapper<ast::expression const> const> operands);
 
   std::unordered_map<std::string, size_type> column_name_to_index;
-  std::optional<std::reference_wrapper<ast::expression const>> _stats_expr;
+  std::optional<std::reference_wrapper<ast::expression const>> _converted_expr;
   // Using std::list or std::deque to avoid reference invalidation
   std::list<ast::column_reference> _col_ref;
   std::list<ast::operation> _operators;
diff --git a/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_100_chunk_stats.snappy.parquet b/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_100_chunk_stats.snappy.parquet
index e1dad1ef8b59edea48aa8c5c41029d9a70babe8f..7dc2cee21ae5e3414f4f23edd0dc31ad03a3976c 100644
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diff --git a/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_500_chunk_stats.snappy.parquet b/python/cudf/cudf/tests/data/parquet/mixed_card_ndv_500_chunk_stats.snappy.parquet
index 746916cf07dc329f95ccd024cd8a2645920b4bf8..3060234d499cd6b614621e19fc55b10c96b2182a 100644
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From 88bf4913713b4ae73c4b45110b976220eca7af26 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 05:11:18 +0000
Subject: [PATCH 50/82] Minor, add const

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 5054051b042..7f7db91d1c4 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -499,7 +499,7 @@ aggregate_reader_metadata::apply_bloom_filters(
     cudf::detail::make_device_uvector_async(h_bloom_filter_spans, stream, mr);
 
   // Create a bloom filter query table caster.
-  bloom_filter_caster bloom_filter_col{
+  bloom_filter_caster const bloom_filter_col{
     bloom_filter_spans, parquet_types, total_row_groups, equality_col_schemas.size()};
 
   // Converts bloom filter membership for equality predicate columns to a table

From 9ca42c62eab9acdb52148e479e14516a10200cf9 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 05:42:55 +0000
Subject: [PATCH 51/82] Move bloom filter test to parquet test

---
 cpp/tests/CMakeLists.txt                                    | 6 +++---
 .../parquet_bloom_filter_test.cu}                           | 0
 2 files changed, 3 insertions(+), 3 deletions(-)
 rename cpp/tests/{hashing/bloom_filter_test.cu => io/parquet_bloom_filter_test.cu} (100%)

diff --git a/cpp/tests/CMakeLists.txt b/cpp/tests/CMakeLists.txt
index 94a5063d150..2e30e390032 100644
--- a/cpp/tests/CMakeLists.txt
+++ b/cpp/tests/CMakeLists.txt
@@ -182,7 +182,6 @@ ConfigureTest(DATETIME_OPS_TEST datetime/datetime_ops_test.cpp)
 # * hashing tests ---------------------------------------------------------------------------------
 ConfigureTest(
   HASHING_TEST
-  hashing/bloom_filter_test.cu
   hashing/md5_test.cpp
   hashing/murmurhash3_x86_32_test.cpp
   hashing/murmurhash3_x64_128_test.cpp
@@ -315,14 +314,15 @@ ConfigureTest(
 )
 ConfigureTest(
   PARQUET_TEST
-  io/parquet_test.cpp
+  io/parquet_bloom_filter_test.cu
   io/parquet_chunked_reader_test.cu
   io/parquet_chunked_writer_test.cpp
   io/parquet_common.cpp
   io/parquet_misc_test.cpp
   io/parquet_reader_test.cpp
-  io/parquet_writer_test.cpp
+  io/parquet_test.cpp
   io/parquet_v2_test.cpp
+  io/parquet_writer_test.cpp
   GPUS 1
   PERCENT 30
 )
diff --git a/cpp/tests/hashing/bloom_filter_test.cu b/cpp/tests/io/parquet_bloom_filter_test.cu
similarity index 100%
rename from cpp/tests/hashing/bloom_filter_test.cu
rename to cpp/tests/io/parquet_bloom_filter_test.cu

From 84c24c16c8374c9951827b0b5890e5c0e72e8901 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 06:04:27 +0000
Subject: [PATCH 52/82] Minor updates

---
 cpp/tests/io/parquet_bloom_filter_test.cu | 20 +++++++++++---------
 1 file changed, 11 insertions(+), 9 deletions(-)

diff --git a/cpp/tests/io/parquet_bloom_filter_test.cu b/cpp/tests/io/parquet_bloom_filter_test.cu
index 9ca76c085b6..c290de4568a 100644
--- a/cpp/tests/io/parquet_bloom_filter_test.cu
+++ b/cpp/tests/io/parquet_bloom_filter_test.cu
@@ -31,9 +31,9 @@
 
 using StringType = cudf::string_view;
 
-class BloomFilterTest : public cudf::test::BaseFixture {};
+class ParquetBloomFilterTest : public cudf::test::BaseFixture {};
 
-TEST_F(BloomFilterTest, TestStrings)
+TEST_F(ParquetBloomFilterTest, TestStrings)
 {
   using key_type    = StringType;
   using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
@@ -43,8 +43,8 @@ TEST_F(BloomFilterTest, TestStrings)
   std::size_t constexpr num_filter_blocks = 4;
   auto stream                             = cudf::get_default_stream();
 
-  // strings data
-  auto data = cudf::test::strings_column_wrapper(
+  // strings keys to insert
+  auto keys = cudf::test::strings_column_wrapper(
     {"seventh",    "fifteenth",   "second",      "tenth",      "fifth",       "first",
      "seventh",    "tenth",       "ninth",       "ninth",      "seventeenth", "eighteenth",
      "thirteenth", "fifth",       "fourth",      "twelfth",    "second",      "second",
@@ -54,7 +54,8 @@ TEST_F(BloomFilterTest, TestStrings)
      "seventh",    "tenth",       "fourteenth",  "first",      "fifth",       "fifth",
      "tenth",      "thirteenth",  "fourteenth",  "third",      "third",       "sixth",
      "first",      "third"});
-  auto d_column = cudf::column_device_view::create(data);
+
+  auto d_keys = cudf::column_device_view::create(keys);
 
   // Spawn a bloom filter
   cuco::bloom_filter<key_type,
@@ -69,15 +70,16 @@ TEST_F(BloomFilterTest, TestStrings)
            stream};
 
   // Add strings to the bloom filter
-  filter.add(d_column->begin<key_type>(), d_column->end<key_type>(), stream);
+  filter.add(d_keys->begin<key_type>(), d_keys->end<key_type>(), stream);
 
   // Number of words in the filter
   cudf::size_type const num_words = filter.block_extent() * filter.words_per_block;
 
-  auto const output = cudf::column_view{
+  // Filter bitset as a column
+  auto const bitset = cudf::column_view{
     cudf::data_type{cudf::type_id::UINT32}, num_words, filter.data(), nullptr, 0, 0, {}};
 
-  // Expected filter bitset words computed using Arrow implementation here:
+  // Expected filter bitset words computed using Arrow's implementation here:
   // https://godbolt.org/z/oKfqcPWbY
   auto expected = cudf::test::fixed_width_column_wrapper<word_type>(
     {4194306U,    4194305U,    2359296U,  1073774592U, 524544U,    1024U,      268443648U,
@@ -87,5 +89,5 @@ TEST_F(BloomFilterTest, TestStrings)
      2216738864U, 587333888U,  4219272U,  873463873U});
 
   // Check the bitset for equality
-  CUDF_TEST_EXPECT_COLUMNS_EQUAL(output, expected);
+  CUDF_TEST_EXPECT_COLUMNS_EQUAL(bitset, expected);
 }

From 0c0503174b78220b2e99ac71f242cdd8caa1fced Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 17:57:54 +0000
Subject: [PATCH 53/82] Minor

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 7f7db91d1c4..9bebd6bcabf 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -485,13 +485,12 @@ aggregate_reader_metadata::apply_bloom_filters(
   // Create spans from bloom filter bitset buffers
   std::vector<cudf::device_span<cuda::std::byte>> h_bloom_filter_spans;
   h_bloom_filter_spans.reserve(bloom_filter_data.size());
-  std::transform(thrust::make_counting_iterator<size_t>(0),
-                 thrust::make_counting_iterator<size_t>(bloom_filter_data.size()),
+  std::transform(bloom_filter_data.begin(),
+                 bloom_filter_data.end(),
                  std::back_inserter(h_bloom_filter_spans),
-                 [&](auto const filter_idx) {
+                 [&](auto& buffer) {
                    return cudf::device_span<cuda::std::byte>{
-                     static_cast<cuda::std::byte*>(bloom_filter_data[filter_idx].data()),
-                     bloom_filter_data[filter_idx].size()};
+                     static_cast<cuda::std::byte*>(buffer.data()), buffer.size()};
                  });
 
   // Copy bloom filter bitset spans to device

From 09560c56cb84c6eac103e34a713ed8bb2f739a7a Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 18:27:13 +0000
Subject: [PATCH 54/82] Logical and between bloom filter and stats

---
 cpp/src/io/parquet/predicate_pushdown.cpp | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index 5ff8645b569..57c168d4c56 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -419,7 +419,7 @@ std::reference_wrapper<ast::expression const> combined_expression_converter::vis
           _operators.emplace_back(ast_operator::LESS_EQUAL, vmin, operands[1].get());
         auto const& op2 =
           _operators.emplace_back(ast_operator::GREATER_EQUAL, vmax, operands[1].get());
-        _operators.emplace_back(ast::ast_operator::LOGICAL_AND, op1, op2);
+        auto const& stats_op = _operators.emplace_back(ast::ast_operator::LOGICAL_AND, op1, op2);
 
         // Use this input column's bloom filter membership column as well if available.
         if (_has_bloom_filters) {
@@ -433,9 +433,12 @@ std::reference_wrapper<ast::expression const> combined_expression_converter::vis
           col_literal_offset += std::distance(equality_literals.cbegin(), literal_iter);
 
           // Evaluate boolean is_true(value) expression as NOT(NOT(value))
-          auto const& value = _col_ref.emplace_back(col_literal_offset);
-          auto const& op    = _operators.emplace_back(ast_operator::NOT, value);
-          _operators.emplace_back(ast_operator::NOT, op);
+          auto const& value           = _col_ref.emplace_back(col_literal_offset);
+          auto const& op              = _operators.emplace_back(ast_operator::NOT, value);
+          auto const& bloom_filter_op = _operators.emplace_back(ast_operator::NOT, op);
+
+          // Logical and between stats and bloom filter operators
+          _operators.emplace_back(ast_operator::LOGICAL_AND, stats_op, bloom_filter_op);
         }
         break;
       }

From 21f4412d7ebcce746fac06b24f49325874a93daa Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 19:14:56 +0000
Subject: [PATCH 55/82] Revert merging converted AST tables.

---
 cpp/src/io/parquet/bloom_filter_reader.cu  | 179 ++++++++++-
 cpp/src/io/parquet/predicate_pushdown.cpp  | 353 ++++++++++-----------
 cpp/src/io/parquet/reader_impl_helpers.hpp |  89 +-----
 3 files changed, 351 insertions(+), 270 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 9bebd6bcabf..d01ff0c1c63 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -162,22 +162,47 @@ struct bloom_filter_caster {
  * @brief Collects lists of equality predicate literals in the AST expression, one list per input
  * table column. This is used in row group filtering based on bloom filters.
  */
-class equality_literals_collector : public combined_expression_converter {
+class equality_literals_collector : public ast::detail::expression_transformer {
  public:
+  equality_literals_collector() = default;
+
   equality_literals_collector(ast::expression const& expr, cudf::size_type num_input_columns)
+    : _num_input_columns{num_input_columns}
   {
-    _num_input_columns = num_input_columns;
     _equality_literals.resize(_num_input_columns);
     expr.accept(*this);
   }
 
-  // Bring all overloads of `visit` from combined_expression_converter into scope
-  using combined_expression_converter::visit;
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::literal const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override
+  {
+    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(expr);
+    return expr;
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override
+  {
+    CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
+                 "BloomfilterAST supports only left table");
+    CUDF_EXPECTS(expr.get_column_index() < _num_input_columns,
+                 "Column index cannot be more than number of columns in the table");
+    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(expr);
+    return expr;
+  }
 
   /**
-   * @brief Delete converted expression getter as no longer needed
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_name_reference const& )
    */
-  [[nodiscard]] std::reference_wrapper<ast::expression const> get_converted_expr() = delete;
+  std::reference_wrapper<ast::expression const> visit(
+    ast::column_name_reference const& expr) override
+  {
+    CUDF_FAIL("Column name reference is not supported in BloomfilterAST");
+  }
 
   /**
    * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
@@ -210,7 +235,7 @@ class equality_literals_collector : public combined_expression_converter {
         _operators.emplace_back(op, new_operands.front());
       }
     }
-    _converted_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(_operators.back());
     return std::reference_wrapper<ast::expression const>(_operators.back());
   }
 
@@ -223,6 +248,121 @@ class equality_literals_collector : public combined_expression_converter {
   {
     return _equality_literals;
   }
+
+ protected:
+  std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
+    cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
+  {
+    std::vector<std::reference_wrapper<ast::expression const>> transformed_operands;
+    for (auto const& operand : operands) {
+      auto const new_operand = operand.get().accept(*this);
+      transformed_operands.push_back(new_operand);
+    }
+    return transformed_operands;
+  }
+  std::optional<std::reference_wrapper<ast::expression const>> _bloom_filter_expr;
+  std::vector<std::vector<ast::literal*>> _equality_literals;
+  std::list<ast::column_reference> _col_ref;
+  std::list<ast::operation> _operators;
+  size_type _num_input_columns;
+};
+
+/**
+ * @brief Converts AST expression to bloom filter membership (BloomfilterAST) expression.
+ * This is used in row group filtering based on equality predicate.
+ */
+class bloom_filter_expression_converter : public equality_literals_collector {
+ public:
+  bloom_filter_expression_converter(
+    ast::expression const& expr,
+    size_type num_input_columns,
+    std::vector<std::vector<ast::literal*>> const& equality_literals)
+  {
+    // Set the num columns and copy equality literals
+    _num_input_columns = num_input_columns;
+    _equality_literals = equality_literals;
+
+    // Compute and store columns literals offsets
+    _col_literals_offsets.reserve(_num_input_columns + 1);
+    _col_literals_offsets.emplace_back(0);
+
+    std::transform(equality_literals.begin(),
+                   equality_literals.end(),
+                   std::back_inserter(_col_literals_offsets),
+                   [&](auto const& col_literal_map) {
+                     return _col_literals_offsets.back() +
+                            static_cast<cudf::size_type>(col_literal_map.size());
+                   });
+
+    // Add this visitor
+    expr.accept(*this);
+  }
+
+  /**
+   * @brief Delete equality literals getter as no longer needed
+   */
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() = delete;
+
+  // Bring all overloads of `visit` from equality_predicate_collector into scope
+  using equality_literals_collector::visit;
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override
+  {
+    using cudf::ast::ast_operator;
+    auto const operands = expr.get_operands();
+    auto const op       = expr.get_operator();
+
+    if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
+      // First operand should be column reference, second should be literal.
+      CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
+                   "Only binary operations are supported on column reference");
+      CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
+                   "Second operand of binary operation with column reference must be a literal");
+      v->accept(*this);
+
+      if (op == ast_operator::EQUAL) {
+        // Search the literal in this input column's equality literals list and add to the offset.
+        auto const col_idx            = v->get_column_index();
+        auto const& equality_literals = _equality_literals[col_idx];
+        auto col_literal_offset       = _col_literals_offsets[col_idx];
+        auto const literal_iter       = std::find(equality_literals.cbegin(),
+                                            equality_literals.cend(),
+                                            dynamic_cast<ast::literal const*>(&operands[1].get()));
+        CUDF_EXPECTS(literal_iter != equality_literals.end(), "Could not find the literal ptr");
+        col_literal_offset += std::distance(equality_literals.cbegin(), literal_iter);
+
+        // Evaluate boolean is_true(value) expression as NOT(NOT(value))
+        auto const& value = _col_ref.emplace_back(col_literal_offset);
+        auto const& op    = _operators.emplace_back(ast_operator::NOT, value);
+        _operators.emplace_back(ast_operator::NOT, op);
+      }
+    } else {
+      auto new_operands = visit_operands(operands);
+      if (cudf::ast::detail::ast_operator_arity(op) == 2) {
+        _operators.emplace_back(op, new_operands.front(), new_operands.back());
+      } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
+        _operators.emplace_back(op, new_operands.front());
+      }
+    }
+    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    return std::reference_wrapper<ast::expression const>(_operators.back());
+  }
+
+  /**
+   * @brief Returns the AST to apply on bloom filters mmebership.
+   *
+   * @return AST operation expression
+   */
+  [[nodiscard]] std::reference_wrapper<ast::expression const> get_bloom_filter_expr() const
+  {
+    return _bloom_filter_expr.value().get();
+  }
+
+ private:
+  std::vector<cudf::size_type> _col_literals_offsets;
 };
 
 /**
@@ -435,8 +575,7 @@ std::vector<Type> aggregate_reader_metadata::get_parquet_types(
   return parquet_types;
 }
 
-std::pair<std::vector<std::unique_ptr<cudf::column>>, std::vector<std::vector<ast::literal*>>>
-aggregate_reader_metadata::apply_bloom_filters(
+std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::apply_bloom_filters(
   host_span<std::unique_ptr<datasource> const> sources,
   host_span<std::vector<size_type> const> input_row_group_indices,
   host_span<data_type const> output_dtypes,
@@ -469,7 +608,7 @@ aggregate_reader_metadata::apply_bloom_filters(
   std::vector<std::unique_ptr<cudf::column>> bloom_filter_membership_columns;
 
   // Return early if no column with equality predicate(s)
-  if (equality_col_schemas.empty()) { return {}; }
+  if (equality_col_schemas.empty()) { return std::nullopt; }
 
   // Read a vector of bloom filter bitset device buffers for all column with equality
   // predicate(s) across all row groups
@@ -477,12 +616,12 @@ aggregate_reader_metadata::apply_bloom_filters(
     sources, input_row_group_indices, equality_col_schemas, total_row_groups, stream);
 
   // No bloom filter buffers, return the original row group indices
-  if (bloom_filter_data.empty()) { return {}; }
+  if (bloom_filter_data.empty()) { return std::nullopt; }
 
   // Get parquet types for the predicate columns
   auto const parquet_types = get_parquet_types(input_row_group_indices, equality_col_schemas);
 
-  // Create spans from bloom filter bitset buffers
+  // Create spans from bloom filter bitset buffers to use in cuco::bloom_filter_ref.
   std::vector<cudf::device_span<cuda::std::byte>> h_bloom_filter_spans;
   h_bloom_filter_spans.reserve(bloom_filter_data.size());
   std::transform(bloom_filter_data.begin(),
@@ -524,8 +663,20 @@ aggregate_reader_metadata::apply_bloom_filters(
       }
       equality_col_idx++;
     });
-
-  return {std::move(bloom_filter_membership_columns), std::move(equality_literals)};
+  auto bloom_filter_membership_table = cudf::table(std::move(bloom_filter_membership_columns));
+
+  // Convert AST to BloomfilterAST expression with reference to bloom filter membership
+  // in above `bloom_filter_membership_table`
+  bloom_filter_expression_converter bloom_filter_expr{
+    filter.get(), num_input_columns, equality_literals};
+
+  // Filter bloom filter membership table with the BloomfilterAST expression and collect
+  // filtered row group indices
+  return collect_filtered_row_group_indices(bloom_filter_membership_table,
+                                            bloom_filter_expr.get_bloom_filter_expr(),
+                                            input_row_group_indices,
+                                            stream,
+                                            mr);
 }
 
 }  // namespace cudf::io::parquet::detail
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index 57c168d4c56..93edbb161ed 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -246,6 +246,150 @@ struct stats_caster {
   }
 };
 
+/**
+ * @brief Converts AST expression to StatsAST for comparing with column statistics
+ * This is used in row group filtering based on predicate.
+ * statistics min value of a column is referenced by column_index*2
+ * statistics max value of a column is referenced by column_index*2+1
+ *
+ */
+class stats_expression_converter : public ast::detail::expression_transformer {
+ public:
+  stats_expression_converter(ast::expression const& expr, size_type const& num_columns)
+    : _num_columns{num_columns}
+  {
+    expr.accept(*this);
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::literal const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override
+  {
+    _stats_expr = std::reference_wrapper<ast::expression const>(expr);
+    return expr;
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override
+  {
+    CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
+                 "Statistics AST supports only left table");
+    CUDF_EXPECTS(expr.get_column_index() < _num_columns,
+                 "Column index cannot be more than number of columns in the table");
+    _stats_expr = std::reference_wrapper<ast::expression const>(expr);
+    return expr;
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::column_name_reference const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(
+    ast::column_name_reference const& expr) override
+  {
+    CUDF_FAIL("Column name reference is not supported in statistics AST");
+  }
+
+  /**
+   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
+   */
+  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override
+  {
+    using cudf::ast::ast_operator;
+    auto const operands = expr.get_operands();
+    auto const op       = expr.get_operator();
+
+    if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
+      // First operand should be column reference, second should be literal.
+      CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
+                   "Only binary operations are supported on column reference");
+      CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
+                   "Second operand of binary operation with column reference must be a literal");
+      v->accept(*this);
+      auto const col_index = v->get_column_index();
+      switch (op) {
+        /* transform to stats conditions. op(col, literal)
+        col1 == val --> vmin <= val && vmax >= val
+        col1 != val --> !(vmin == val && vmax == val)
+        col1 >  val --> vmax > val
+        col1 <  val --> vmin < val
+        col1 >= val --> vmax >= val
+        col1 <= val --> vmin <= val
+        */
+        case ast_operator::EQUAL: {
+          auto const& vmin = _col_ref.emplace_back(col_index * 2);
+          auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
+          auto const& op1 =
+            _operators.emplace_back(ast_operator::LESS_EQUAL, vmin, operands[1].get());
+          auto const& op2 =
+            _operators.emplace_back(ast_operator::GREATER_EQUAL, vmax, operands[1].get());
+          _operators.emplace_back(ast::ast_operator::LOGICAL_AND, op1, op2);
+          break;
+        }
+        case ast_operator::NOT_EQUAL: {
+          auto const& vmin = _col_ref.emplace_back(col_index * 2);
+          auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
+          auto const& op1  = _operators.emplace_back(ast_operator::NOT_EQUAL, vmin, vmax);
+          auto const& op2 =
+            _operators.emplace_back(ast_operator::NOT_EQUAL, vmax, operands[1].get());
+          _operators.emplace_back(ast_operator::LOGICAL_OR, op1, op2);
+          break;
+        }
+        case ast_operator::LESS: [[fallthrough]];
+        case ast_operator::LESS_EQUAL: {
+          auto const& vmin = _col_ref.emplace_back(col_index * 2);
+          _operators.emplace_back(op, vmin, operands[1].get());
+          break;
+        }
+        case ast_operator::GREATER: [[fallthrough]];
+        case ast_operator::GREATER_EQUAL: {
+          auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
+          _operators.emplace_back(op, vmax, operands[1].get());
+          break;
+        }
+        default: CUDF_FAIL("Unsupported operation in Statistics AST");
+      };
+    } else {
+      auto new_operands = visit_operands(operands);
+      if (cudf::ast::detail::ast_operator_arity(op) == 2) {
+        _operators.emplace_back(op, new_operands.front(), new_operands.back());
+      } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
+        _operators.emplace_back(op, new_operands.front());
+      }
+    }
+    _stats_expr = std::reference_wrapper<ast::expression const>(_operators.back());
+    return std::reference_wrapper<ast::expression const>(_operators.back());
+  }
+
+  /**
+   * @brief Returns the AST to apply on Column chunk statistics.
+   *
+   * @return AST operation expression
+   */
+  [[nodiscard]] std::reference_wrapper<ast::expression const> get_stats_expr() const
+  {
+    return _stats_expr.value().get();
+  }
+
+ private:
+  std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
+    cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
+  {
+    std::vector<std::reference_wrapper<ast::expression const>> transformed_operands;
+    for (auto const& operand : operands) {
+      auto const new_operand = operand.get().accept(*this);
+      transformed_operands.push_back(new_operand);
+    }
+    return transformed_operands;
+  }
+  std::optional<std::reference_wrapper<ast::expression const>> _stats_expr;
+  size_type _num_columns;
+  std::list<ast::column_reference> _col_ref;
+  std::list<ast::operation> _operators;
+};
+
 }  // namespace
 
 std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::filter_row_groups(
@@ -256,9 +400,6 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
   std::reference_wrapper<ast::expression const> filter,
   rmm::cuda_stream_view stream) const
 {
-  // Number of input table columns
-  auto const num_input_columns = static_cast<cudf::size_type>(output_dtypes.size());
-
   auto mr = cudf::get_current_device_resource_ref();
   // Create row group indices.
   std::vector<std::vector<size_type>> all_row_group_indices;
@@ -309,183 +450,39 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
     columns.push_back(std::move(min_col));
     columns.push_back(std::move(max_col));
   }
+  auto stats_table = cudf::table(std::move(columns));
 
-  // Apply bloom filter membership to row groups for each equality predicate column, literal pair
-  // and get corresponding boolean columns.
-  auto [bloom_filter_membership_cols, equality_literals] =
-    apply_bloom_filters(sources,
-                        input_row_group_indices,
-                        output_dtypes,
-                        output_column_schemas,
-                        filter,
-                        total_row_groups,
-                        stream);
-
-  // Check if we have any bloom filter membership columns
-  auto const has_bloom_filters = not bloom_filter_membership_cols.empty();
-
-  // Append bloom filter membership columns to stats columns to get combined columns if needed
-  if (has_bloom_filters) {
-    columns.insert(columns.end(),
-                   std::make_move_iterator(bloom_filter_membership_cols.begin()),
-                   std::make_move_iterator(bloom_filter_membership_cols.end()));
-  }
-
-  auto combined_table = cudf::table(std::move(columns));
-
-  // Convert AST to a CombinedAST (StatsAST and BloomfilterAST) expression
-  combined_expression_converter combined_expr{
-    filter.get(), num_input_columns, equality_literals, has_bloom_filters};
-
-  // Filter combined table with the AST expression and collect filtered row group indices
-  return collect_filtered_row_group_indices(
-    combined_table, combined_expr.get_converted_expr(), input_row_group_indices, stream, mr);
-}
-
-// Convert AST expression to a CombinedAST (StatsAST and BloomfilterAST)
-combined_expression_converter::combined_expression_converter(
-  ast::expression const& expr,
-  size_type num_input_columns,
-  std::vector<std::vector<ast::literal*>> const& equality_literals,
-  bool has_bloom_filters)
-  : _has_bloom_filters{has_bloom_filters}
-{
-  // Set the num columns and copy equality literals
-  _num_input_columns = num_input_columns;
-  _equality_literals = equality_literals;
-
-  // Compute and store columns literals offsets
-  _col_literals_offsets.reserve(_num_input_columns + 1);
-  _col_literals_offsets.emplace_back(0);
-
-  std::transform(equality_literals.begin(),
-                 equality_literals.end(),
-                 std::back_inserter(_col_literals_offsets),
-                 [&](auto const& col_literal_map) {
-                   return _col_literals_offsets.back() +
-                          static_cast<cudf::size_type>(col_literal_map.size());
-                 });
-
-  // Add this visitor
-  expr.accept(*this);
-}
-
-std::reference_wrapper<ast::expression const> combined_expression_converter::visit(
-  ast::literal const& expr)
-{
-  _converted_expr = std::reference_wrapper<ast::expression const>(expr);
-  return expr;
-}
-
-std::reference_wrapper<ast::expression const> combined_expression_converter::visit(
-  ast::column_reference const& expr)
-{
-  CUDF_EXPECTS(expr.get_table_source() == ast::table_reference::LEFT,
-               "CombinedAST (Stats and Bloomfilter) supports only left table");
-  CUDF_EXPECTS(expr.get_column_index() < _num_input_columns,
-               "Column index cannot be more than number of columns in the table");
-  _converted_expr = std::reference_wrapper<ast::expression const>(expr);
-  return expr;
-}
-
-std::reference_wrapper<ast::expression const> combined_expression_converter::visit(
-  ast::operation const& expr)
-{
-  using cudf::ast::ast_operator;
-  auto const operands = expr.get_operands();
-  auto const op       = expr.get_operator();
-
-  if (auto* v = dynamic_cast<ast::column_reference const*>(&operands[0].get())) {
-    // First operand should be column reference, second should be literal.
-    CUDF_EXPECTS(cudf::ast::detail::ast_operator_arity(op) == 2,
-                 "Only binary operations are supported on column reference");
-    CUDF_EXPECTS(dynamic_cast<ast::literal const*>(&operands[1].get()) != nullptr,
-                 "Second operand of binary operation with column reference must be a literal");
-    v->accept(*this);
-    auto const col_index = v->get_column_index();
-    switch (op) {
-      /* transform to stats conditions. op(col, literal)
-      col1 == val --> vmin <= val && vmax >= val && bloom_filter[col1, val].contains(val)
-      col1 != val --> !(vmin == val && vmax == val)
-      col1 >  val --> vmax > val
-      col1 <  val --> vmin < val
-      col1 >= val --> vmax >= val
-      col1 <= val --> vmin <= val
-      */
-      case ast_operator::EQUAL: {
-        auto const& vmin = _col_ref.emplace_back(col_index * 2);
-        auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
-        auto const& op1 =
-          _operators.emplace_back(ast_operator::LESS_EQUAL, vmin, operands[1].get());
-        auto const& op2 =
-          _operators.emplace_back(ast_operator::GREATER_EQUAL, vmax, operands[1].get());
-        auto const& stats_op = _operators.emplace_back(ast::ast_operator::LOGICAL_AND, op1, op2);
-
-        // Use this input column's bloom filter membership column as well if available.
-        if (_has_bloom_filters) {
-          auto const& equality_literals = _equality_literals[col_index];
-          auto col_literal_offset = (_num_input_columns * 2) + _col_literals_offsets[col_index];
-          auto const literal_iter =
-            std::find(equality_literals.cbegin(),
-                      equality_literals.cend(),
-                      dynamic_cast<ast::literal const*>(&operands[1].get()));
-          CUDF_EXPECTS(literal_iter != equality_literals.end(), "Could not find the literal ptr");
-          col_literal_offset += std::distance(equality_literals.cbegin(), literal_iter);
-
-          // Evaluate boolean is_true(value) expression as NOT(NOT(value))
-          auto const& value           = _col_ref.emplace_back(col_literal_offset);
-          auto const& op              = _operators.emplace_back(ast_operator::NOT, value);
-          auto const& bloom_filter_op = _operators.emplace_back(ast_operator::NOT, op);
-
-          // Logical and between stats and bloom filter operators
-          _operators.emplace_back(ast_operator::LOGICAL_AND, stats_op, bloom_filter_op);
-        }
-        break;
-      }
-      case ast_operator::NOT_EQUAL: {
-        auto const& vmin = _col_ref.emplace_back(col_index * 2);
-        auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
-        auto const& op1  = _operators.emplace_back(ast_operator::NOT_EQUAL, vmin, vmax);
-        auto const& op2 = _operators.emplace_back(ast_operator::NOT_EQUAL, vmax, operands[1].get());
-        _operators.emplace_back(ast_operator::LOGICAL_OR, op1, op2);
-        break;
-      }
-      case ast_operator::LESS: [[fallthrough]];
-      case ast_operator::LESS_EQUAL: {
-        auto const& vmin = _col_ref.emplace_back(col_index * 2);
-        _operators.emplace_back(op, vmin, operands[1].get());
-        break;
-      }
-      case ast_operator::GREATER: [[fallthrough]];
-      case ast_operator::GREATER_EQUAL: {
-        auto const& vmax = _col_ref.emplace_back(col_index * 2 + 1);
-        _operators.emplace_back(op, vmax, operands[1].get());
-        break;
-      }
-      default: CUDF_FAIL("Unsupported operation in CombinedAST");
-    };
-  } else {
-    auto new_operands = visit_operands(operands);
-    if (cudf::ast::detail::ast_operator_arity(op) == 2) {
-      _operators.emplace_back(op, new_operands.front(), new_operands.back());
-    } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
-      _operators.emplace_back(op, new_operands.front());
-    }
-  }
-  _converted_expr = std::reference_wrapper<ast::expression const>(_operators.back());
-  return std::reference_wrapper<ast::expression const>(_operators.back());
-}
+  // Converts AST to StatsAST with reference to min, max columns in above `stats_table`.
+  stats_expression_converter const stats_expr{filter.get(),
+                                              static_cast<size_type>(output_dtypes.size())};
+  auto stats_ast     = stats_expr.get_stats_expr();
+  auto predicate_col = cudf::detail::compute_column(stats_table, stats_ast.get(), stream, mr);
+  auto predicate     = predicate_col->view();
+  CUDF_EXPECTS(predicate.type().id() == cudf::type_id::BOOL8,
+               "Filter expression must return a boolean column");
 
-std::vector<std::reference_wrapper<ast::expression const>>
-combined_expression_converter::visit_operands(
-  cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
-{
-  std::vector<std::reference_wrapper<ast::expression const>> transformed_operands;
-  for (auto const& operand : operands) {
-    auto const new_operand = operand.get().accept(*this);
-    transformed_operands.push_back(new_operand);
-  }
-  return transformed_operands;
+  // Filter stats table with StatsAST expression and collect filtered row group indices
+  auto const filtered_row_group_indices = collect_filtered_row_group_indices(
+    stats_table, stats_expr.get_stats_expr(), input_row_group_indices, stream, mr);
+
+  // Span of row groups to apply bloom filtering on.
+  auto const bloom_filter_input_row_groups =
+    filtered_row_group_indices.has_value()
+      ? host_span<std::vector<size_type> const>(filtered_row_group_indices.value())
+      : input_row_group_indices;
+
+  // Apply bloom filtering on the bloom filter input row groups
+  auto const bloom_filtered_row_groups = apply_bloom_filters(sources,
+                                                             bloom_filter_input_row_groups,
+                                                             output_dtypes,
+                                                             output_column_schemas,
+                                                             filter,
+                                                             total_row_groups,
+                                                             stream);
+
+  // Return bloom filtered row group indices iff collected
+  return bloom_filtered_row_groups.has_value() ? bloom_filtered_row_groups
+                                               : filtered_row_group_indices;
 }
 
 // convert column named expression to column index reference expression
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 859d9aadc94..e717ee5c126 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -372,28 +372,26 @@ class aggregate_reader_metadata {
     rmm::cuda_stream_view stream) const;
 
   /**
-   * @brief Computes bloom filter membership for the row groups based on predicate filter
+   * @brief Filters the row groups using bloom filters
    *
    * @param sources Dataset sources
    * @param row_group_indices Lists of input row groups to read, one per source
    * @param output_dtypes Datatypes of of output columns
    * @param output_column_schemas schema indices of output columns
    * @param filter AST expression to filter row groups based on bloom filter membership
-   * @param total_row_groups Total number of row groups across all input sources.
+   * @param total_row_groups Total number of row groups across all data sources
    * @param stream CUDA stream used for device memory operations and kernel launches
    *
-   * @return A pair of list of bloom filter membership columns and a list of pointers to (equality
-   * predicate) literals associated with each input column.
+   * @return Filtered row group indices, if any is filtered
    */
-  [[nodiscard]] std::pair<std::vector<std::unique_ptr<cudf::column>>,
-                          std::vector<std::vector<ast::literal*>>>
-  apply_bloom_filters(host_span<std::unique_ptr<datasource> const> sources,
-                      host_span<std::vector<size_type> const> input_row_group_indices,
-                      host_span<data_type const> output_dtypes,
-                      host_span<int const> output_column_schemas,
-                      std::reference_wrapper<ast::expression const> filter,
-                      size_t total_row_groups,
-                      rmm::cuda_stream_view stream) const;
+  [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> apply_bloom_filters(
+    host_span<std::unique_ptr<datasource> const> sources,
+    host_span<std::vector<size_type> const> input_row_group_indices,
+    host_span<data_type const> output_dtypes,
+    host_span<int const> output_column_schemas,
+    std::reference_wrapper<ast::expression const> filter,
+    size_t total_row_groups,
+    rmm::cuda_stream_view stream) const;
 
   /**
    * @brief Filters and reduces down to a selection of row groups
@@ -445,71 +443,6 @@ class aggregate_reader_metadata {
                  type_id timestamp_type_id);
 };
 
-/**
- * @brief Converts AST expression to a CombinedAST (StatsAST and BloomfilterAST) for comparing with
- * column statistics and testing bloom filter membership altogether. This is used in row group
- * filtering based on predicate.
- *
- * statistics min value of a column is referenced by column_index*2
- * statistics max value of a column is referenced by column_index*2+1
- * bloom filter membership of each (column, literal) pair is appended to the end of stats.
- *
- */
-class combined_expression_converter : public ast::detail::expression_transformer {
- public:
-  combined_expression_converter() = default;
-  combined_expression_converter(ast::expression const& expr,
-                                size_type num_input_columns,
-                                std::vector<std::vector<ast::literal*>> const& equality_literals,
-                                bool has_bloom_filters);
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::literal const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override;
-
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::column_reference const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::column_reference const& expr) override;
-
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::column_name_reference const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(
-    ast::column_name_reference const& expr) override
-  {
-    CUDF_FAIL("Column name reference is not supported in CombinedAST");
-  }
-  /**
-   * @copydoc ast::detail::expression_transformer::visit(ast::operation const& )
-   */
-  std::reference_wrapper<ast::expression const> visit(ast::operation const& expr) override;
-  /**
-   * @brief Returns the AST to apply Column chunk statistics and bloom filter membership
-   *
-   * @return AST operation expression
-   */
-  [[nodiscard]] std::reference_wrapper<ast::expression const> get_converted_expr() const
-  {
-    return _converted_expr.value().get();
-  }
-
- protected:
-  std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
-    cudf::host_span<std::reference_wrapper<ast::expression const> const> operands);
-
-  std::optional<std::reference_wrapper<ast::expression const>> _converted_expr;
-  size_type _num_columns;
-  std::list<ast::column_reference> _col_ref;
-  std::list<ast::operation> _operators;
-  std::vector<std::vector<ast::literal*>> _equality_literals;
-  size_type _num_input_columns;
-
- private:
-  bool _has_bloom_filters;
-  std::vector<cudf::size_type> _col_literals_offsets;
-};
-
 /**
  * @brief Converts named columns to index reference columns
  *

From 442de80211a17dde95e1d970ca4afd5a0c7f0047 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 20:09:52 +0000
Subject: [PATCH 56/82] Revert an extra eol

---
 cpp/src/io/parquet/predicate_pushdown.cpp | 1 -
 1 file changed, 1 deletion(-)

diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index 93edbb161ed..7ae671fbf96 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -389,7 +389,6 @@ class stats_expression_converter : public ast::detail::expression_transformer {
   std::list<ast::column_reference> _col_ref;
   std::list<ast::operation> _operators;
 };
-
 }  // namespace
 
 std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::filter_row_groups(

From f7952d45bd339c743bfd813441cb5f01e0e057da Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 20:10:51 +0000
Subject: [PATCH 57/82] Revert extra eol

---
 cpp/src/io/parquet/reader_impl_helpers.cpp | 1 -
 1 file changed, 1 deletion(-)

diff --git a/cpp/src/io/parquet/reader_impl_helpers.cpp b/cpp/src/io/parquet/reader_impl_helpers.cpp
index b9ed0a8c65b..27280de25eb 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.cpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.cpp
@@ -1049,7 +1049,6 @@ aggregate_reader_metadata::select_row_groups(
         host_span<std::vector<size_type> const>(filtered_row_group_indices.value());
     }
   }
-
   std::vector<row_group_info> selection;
   auto [rows_to_skip, rows_to_read] = [&]() {
     if (not row_group_indices.empty()) { return std::pair<int64_t, size_type>{}; }

From 4d0c57031f6bc441063bf2e3b42601d274ab1144 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 22:02:15 +0000
Subject: [PATCH 58/82] Read bloom filter data sync

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 44 +++++++++++------------
 1 file changed, 20 insertions(+), 24 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index d01ff0c1c63..0485321bc44 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -366,7 +366,7 @@ class bloom_filter_expression_converter : public equality_literals_collector {
 };
 
 /**
- * @brief Asynchronously reads bloom filters data to device.
+ * @brief Reads bloom filters data to device.
  *
  * @param sources Dataset sources
  * @param num_chunks Number of total column chunks to read
@@ -375,17 +375,14 @@ class bloom_filter_expression_converter : public equality_literals_collector {
  * @param bloom_filter_sizes Bloom filter sizes for all chunks
  * @param chunk_source_map Association between each column chunk and its source
  * @param stream CUDA stream used for device memory operations and kernel launches
- *
- * @return A future object for reading synchronization
  */
-std::future<void> read_bloom_filter_data_async(
-  host_span<std::unique_ptr<datasource> const> sources,
-  size_t num_chunks,
-  cudf::host_span<rmm::device_buffer> bloom_filter_data,
-  cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
-  cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
-  std::vector<size_type> const& chunk_source_map,
-  rmm::cuda_stream_view stream)
+void read_bloom_filter_data(host_span<std::unique_ptr<datasource> const> sources,
+                            size_t num_chunks,
+                            cudf::host_span<rmm::device_buffer> bloom_filter_data,
+                            cudf::host_span<std::optional<int64_t>> bloom_filter_offsets,
+                            cudf::host_span<std::optional<int32_t>> bloom_filter_sizes,
+                            std::vector<size_type> const& chunk_source_map,
+                            rmm::cuda_stream_view stream)
 {
   // Read tasks for bloom filter data
   std::vector<std::future<size_t>> read_tasks;
@@ -421,9 +418,9 @@ std::future<void> read_bloom_filter_data_async(
 
       // Get the hardcoded words_per_block value from `cuco::arrow_filter_policy` using a temporary
       // `std::byte` key type.
-      auto constexpr words_per_block =
-        cuco::arrow_filter_policy<std::byte,
-                                  cudf::hashing::detail::XXHash_64<std::byte>>::words_per_block;
+      auto constexpr words_per_block = cuco::arrow_filter_policy<
+        cuda::std::byte,
+        cudf::hashing::detail::XXHash_64<cuda::std::byte>>::words_per_block;
 
       // Check if the bloom filter header is valid.
       auto const is_header_valid =
@@ -475,7 +472,7 @@ std::future<void> read_bloom_filter_data_async(
     }
   };
 
-  return std::async(std::launch::async, sync_fn, std::move(read_tasks));
+  std::async(std::launch::async, sync_fn, std::move(read_tasks)).wait();
 }
 
 }  // namespace
@@ -532,15 +529,14 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
     // Vector to hold bloom filter data
     std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);
 
-    // Wait on bloom filter data read tasks
-    read_bloom_filter_data_async(sources,
-                                 num_chunks,
-                                 bloom_filter_data,
-                                 bloom_filter_offsets,
-                                 bloom_filter_sizes,
-                                 chunk_source_map,
-                                 stream)
-      .wait();
+    // Read bloom filter data
+    read_bloom_filter_data(sources,
+                           num_chunks,
+                           bloom_filter_data,
+                           bloom_filter_offsets,
+                           bloom_filter_sizes,
+                           chunk_source_map,
+                           stream);
 
     // Return bloom filter data
     return bloom_filter_data;

From 67c6247fbce934ea5c94cc0a9bdfd966090bbaa2 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <14217455+mhaseeb123@users.noreply.github.com>
Date: Wed, 4 Dec 2024 14:11:04 -0800
Subject: [PATCH 59/82] Update cpp/src/io/parquet/bloom_filter_reader.cu

Co-authored-by: Yunsong Wang <yunsongw@nvidia.com>
---
 cpp/src/io/parquet/bloom_filter_reader.cu | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 0485321bc44..f982b143949 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -82,8 +82,8 @@ struct bloom_filter_caster {
     // Query literal in bloom filters from each column chunk (row group).
     thrust::for_each(
       rmm::exec_policy_nosync(stream),
-      thrust::make_counting_iterator<size_t>(0),
-      thrust::make_counting_iterator(total_row_groups),
+      thrust::counting_iterator<size_t>{0},
+      thrust::counting_iterator{total_row_groups},
       [filter_span          = bloom_filter_spans.data(),
        d_scalar             = literal->get_value(),
        col_idx              = equality_col_idx,

From 40c80b7f89ccd02655ed71e6c7a143490ebaaa37 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 22:17:55 +0000
Subject: [PATCH 60/82] strong type for int96 timestamp

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 0485321bc44..0f44c93dc93 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -55,7 +55,9 @@ struct bloom_filter_caster {
   size_t total_row_groups;
   size_t num_equality_columns;
 
-  template <typename T, bool timestamp_is_int96 = false>
+  enum class is_int96_timestamp : bool { YES, NO };
+
+  template <typename T, is_int96_timestamp IS_INT96_TIMESTAMP = is_int96_timestamp::NO>
   std::unique_ptr<cudf::column> query_bloom_filter(cudf::size_type equality_col_idx,
                                                    cudf::data_type dtype,
                                                    ast::literal const* const literal,
@@ -116,7 +118,8 @@ struct bloom_filter_caster {
 
         // If int96_timestamp type, convert literal to string_view and query bloom
         // filter
-        if constexpr (cuda::std::is_same_v<T, cudf::string_view> and timestamp_is_int96) {
+        if constexpr (cuda::std::is_same_v<T, cudf::string_view> and
+                      IS_INT96_TIMESTAMP == is_int96_timestamp::YES) {
           auto const int128_key = static_cast<__int128_t>(d_scalar.value<int64_t>());
           cudf::string_view probe_key{reinterpret_cast<char const*>(&int128_key), 12};
           results[row_group_idx] = filter.contains(probe_key);
@@ -146,8 +149,8 @@ struct bloom_filter_caster {
       CUDF_FAIL("Compound types don't support equality predicate");
     } else if constexpr (cudf::is_timestamp<T>()) {
       if (parquet_types[equality_col_idx] == Type::INT96) {
-        // For INT96 timestamps, use cudf::string_view type and set timestamp_is_int96
-        return query_bloom_filter<cudf::string_view, true>(
+        // For INT96 timestamps, use cudf::string_view type and set is_int96_timestamp to YES
+        return query_bloom_filter<cudf::string_view, bloom_filter_caster::is_int96_timestamp::YES>(
           equality_col_idx, dtype, literal, stream, mr);
       } else {
         return query_bloom_filter<T>(equality_col_idx, dtype, literal, stream, mr);

From c5f8150408c2258be8d7ea8d079d982d909a89a0 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Wed, 4 Dec 2024 22:22:22 +0000
Subject: [PATCH 61/82] Remove unused header

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 1 -
 1 file changed, 1 deletion(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index a58dd557b75..f03e919e806 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -38,7 +38,6 @@
 #include <thrust/iterator/counting_iterator.h>
 
 #include <future>
-#include <limits>
 #include <numeric>
 #include <optional>
 

From 44652775979d47a6656e4a41aad47a31245c5d68 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <14217455+mhaseeb123@users.noreply.github.com>
Date: Mon, 9 Dec 2024 12:11:49 -0800
Subject: [PATCH 62/82] Apply suggestions from code review

Co-authored-by: Vukasin Milovanovic <vmilovanovic@nvidia.com>
---
 cpp/src/io/parquet/bloom_filter_reader.cu | 18 ++++++++----------
 1 file changed, 8 insertions(+), 10 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index f03e919e806..605389ff75f 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -440,7 +440,7 @@ void read_bloom_filter_data(host_span<std::unique_ptr<datasource> const> sources
 
       // Bloom filter header size
       auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
-      size_t const bitset_size            = static_cast<size_t>(header.num_bytes);
+      auto const bitset_size            = static_cast<size_t>(header.num_bytes);
 
       // Check if we already read in the filter bitset in the initial read.
       if (initial_read_size >= bloom_filter_header_size + bitset_size) {
@@ -593,14 +593,12 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
 
   // Collect schema indices of columns with equality predicate(s)
   std::vector<cudf::size_type> equality_col_schemas;
-  std::for_each(thrust::make_counting_iterator<size_t>(0),
-                thrust::make_counting_iterator(output_column_schemas.size()),
-                [&](auto col_idx) {
-                  // Only for columns that have a non-empty list of literals associated with it
-                  if (equality_literals[col_idx].size()) {
-                    equality_col_schemas.emplace_back(output_column_schemas[col_idx]);
-                  }
-                });
+  thrust::copy_if(thrust::host,
+                  output_column_schemas.begin(), 
+                  output_column_schemas.end(),
+                  equality_literals.begin(),
+                  std::back_inserter(equality_col_schemas),
+                  [](auto& eq_literals) { not return eq_literals.empty(); });
 
   // Read bloom filters and add literal membership columns.
   std::vector<std::unique_ptr<cudf::column>> bloom_filter_membership_columns;
@@ -608,7 +606,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   // Return early if no column with equality predicate(s)
   if (equality_col_schemas.empty()) { return std::nullopt; }
 
-  // Read a vector of bloom filter bitset device buffers for all column with equality
+  // Read a vector of bloom filter bitset device buffers for all columns with equality
   // predicate(s) across all row groups
   auto bloom_filter_data = read_bloom_filters(
     sources, input_row_group_indices, equality_col_schemas, total_row_groups, stream);

From 38887328f6f03ec8c800544dd1b670152acf4093 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Mon, 9 Dec 2024 20:28:10 +0000
Subject: [PATCH 63/82] Apply suggestions

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 605389ff75f..6aa688aefb2 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -440,7 +440,7 @@ void read_bloom_filter_data(host_span<std::unique_ptr<datasource> const> sources
 
       // Bloom filter header size
       auto const bloom_filter_header_size = static_cast<int64_t>(cp.bytecount());
-      auto const bitset_size            = static_cast<size_t>(header.num_bytes);
+      auto const bitset_size              = static_cast<size_t>(header.num_bytes);
 
       // Check if we already read in the filter bitset in the initial read.
       if (initial_read_size >= bloom_filter_header_size + bitset_size) {
@@ -594,15 +594,12 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   // Collect schema indices of columns with equality predicate(s)
   std::vector<cudf::size_type> equality_col_schemas;
   thrust::copy_if(thrust::host,
-                  output_column_schemas.begin(), 
+                  output_column_schemas.begin(),
                   output_column_schemas.end(),
                   equality_literals.begin(),
                   std::back_inserter(equality_col_schemas),
                   [](auto& eq_literals) { not return eq_literals.empty(); });
 
-  // Read bloom filters and add literal membership columns.
-  std::vector<std::unique_ptr<cudf::column>> bloom_filter_membership_columns;
-
   // Return early if no column with equality predicate(s)
   if (equality_col_schemas.empty()) { return std::nullopt; }
 
@@ -632,13 +629,14 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   auto const bloom_filter_spans =
     cudf::detail::make_device_uvector_async(h_bloom_filter_spans, stream, mr);
 
-  // Create a bloom filter query table caster.
+  // Create a bloom filter query table caster
   bloom_filter_caster const bloom_filter_col{
     bloom_filter_spans, parquet_types, total_row_groups, equality_col_schemas.size()};
 
   // Converts bloom filter membership for equality predicate columns to a table
   // containing a column for each `col[i] == literal` predicate to be evaluated.
   // The table contains #sources * #column_chunks_per_src rows.
+  std::vector<std::unique_ptr<cudf::column>> bloom_filter_membership_columns;
   size_t equality_col_idx = 0;
   std::for_each(
     thrust::make_counting_iterator<size_t>(0),
@@ -659,6 +657,8 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
       }
       equality_col_idx++;
     });
+
+  // Create a table from columns
   auto bloom_filter_membership_table = cudf::table(std::move(bloom_filter_membership_columns));
 
   // Convert AST to BloomfilterAST expression with reference to bloom filter membership

From 8bc8927af3241a0da36a02b9b67585ec8db73460 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <14217455+mhaseeb123@users.noreply.github.com>
Date: Mon, 9 Dec 2024 12:32:24 -0800
Subject: [PATCH 64/82] Update cpp/src/io/parquet/reader_impl_helpers.hpp

Co-authored-by: Vukasin Milovanovic <vmilovanovic@nvidia.com>
---
 cpp/src/io/parquet/reader_impl_helpers.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index e717ee5c126..d61ae241504 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -357,7 +357,7 @@ class aggregate_reader_metadata {
    *
    * @param sources Lists of input datasources
    * @param row_group_indices Lists of row groups to read, one per source
-   * @param output_dtypes Datatypes of of output columns
+   * @param output_dtypes Datatypes of output columns
    * @param output_column_schemas schema indices of output columns
    * @param filter AST expression to filter row groups based on Column chunk statistics
    * @param stream CUDA stream used for device memory operations and kernel launches

From d719e65757aaf117945111a041e59df3b7698030 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <14217455+mhaseeb123@users.noreply.github.com>
Date: Mon, 9 Dec 2024 12:32:33 -0800
Subject: [PATCH 65/82] Update cpp/src/io/parquet/reader_impl_helpers.hpp

Co-authored-by: Vukasin Milovanovic <vmilovanovic@nvidia.com>
---
 cpp/src/io/parquet/reader_impl_helpers.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index d61ae241504..b670c1a63d9 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -376,7 +376,7 @@ class aggregate_reader_metadata {
    *
    * @param sources Dataset sources
    * @param row_group_indices Lists of input row groups to read, one per source
-   * @param output_dtypes Datatypes of of output columns
+   * @param output_dtypes Datatypes of output columns
    * @param output_column_schemas schema indices of output columns
    * @param filter AST expression to filter row groups based on bloom filter membership
    * @param total_row_groups Total number of row groups across all data sources

From 03cf07f08b96d414d6555723163f96b5f0f437e0 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Mon, 9 Dec 2024 21:02:43 +0000
Subject: [PATCH 66/82] Move equality_literals instead of copying

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 6aa688aefb2..80e9b5b315e 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -246,7 +246,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
    *
    * @return Vectors of equality literals, one per input table column
    */
-  [[nodiscard]] std::vector<std::vector<ast::literal*>> const get_equality_literals() const
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() const
   {
     return _equality_literals;
   }

From c92d3265b6e530af3a581d205efc25de44c4c432 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Mon, 9 Dec 2024 21:19:06 +0000
Subject: [PATCH 67/82] Minor

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 80e9b5b315e..48f82c6e3d2 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -598,7 +598,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
                   output_column_schemas.end(),
                   equality_literals.begin(),
                   std::back_inserter(equality_col_schemas),
-                  [](auto& eq_literals) { not return eq_literals.empty(); });
+                  [](auto& eq_literals) { return not eq_literals.empty(); });
 
   // Return early if no column with equality predicate(s)
   if (equality_col_schemas.empty()) { return std::nullopt; }

From 82083f994e8d34eed15a875c4e3c8d33dfcef2ce Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 10 Dec 2024 01:52:35 +0000
Subject: [PATCH 68/82] Use spans instead of passing around vectors

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 22 +++++++++++++---------
 1 file changed, 13 insertions(+), 9 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 48f82c6e3d2..0b16332fa0a 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -246,11 +246,14 @@ class equality_literals_collector : public ast::detail::expression_transformer {
    *
    * @return Vectors of equality literals, one per input table column
    */
-  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() const
+  [[nodiscard]] cudf::host_span<std::vector<ast::literal*> const> get_equality_literals() const
   {
-    return _equality_literals;
+    return {_equality_literals};
   }
 
+ private:
+  std::vector<std::vector<ast::literal*>> _equality_literals;
+
  protected:
   std::vector<std::reference_wrapper<ast::expression const>> visit_operands(
     cudf::host_span<std::reference_wrapper<ast::expression const> const> operands)
@@ -263,7 +266,6 @@ class equality_literals_collector : public ast::detail::expression_transformer {
     return transformed_operands;
   }
   std::optional<std::reference_wrapper<ast::expression const>> _bloom_filter_expr;
-  std::vector<std::vector<ast::literal*>> _equality_literals;
   std::list<ast::column_reference> _col_ref;
   std::list<ast::operation> _operators;
   size_type _num_input_columns;
@@ -278,11 +280,11 @@ class bloom_filter_expression_converter : public equality_literals_collector {
   bloom_filter_expression_converter(
     ast::expression const& expr,
     size_type num_input_columns,
-    std::vector<std::vector<ast::literal*>> const& equality_literals)
+    cudf::host_span<std::vector<ast::literal*> const> equality_literals)
+    : _equality_literals{equality_literals}
   {
-    // Set the num columns and copy equality literals
+    // Set the num columns
     _num_input_columns = num_input_columns;
-    _equality_literals = equality_literals;
 
     // Compute and store columns literals offsets
     _col_literals_offsets.reserve(_num_input_columns + 1);
@@ -303,7 +305,8 @@ class bloom_filter_expression_converter : public equality_literals_collector {
   /**
    * @brief Delete equality literals getter as no longer needed
    */
-  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() = delete;
+  [[nodiscard]] cudf::host_span<std::vector<ast::literal*> const> get_equality_literals() const =
+    delete;
 
   // Bring all overloads of `visit` from equality_predicate_collector into scope
   using equality_literals_collector::visit;
@@ -365,6 +368,7 @@ class bloom_filter_expression_converter : public equality_literals_collector {
 
  private:
   std::vector<cudf::size_type> _col_literals_offsets;
+  cudf::host_span<std::vector<ast::literal*> const> _equality_literals;
 };
 
 /**
@@ -588,8 +592,8 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   auto mr = cudf::get_current_device_resource_ref();
 
   // Collect equality literals for each input table column
-  auto const equality_literals =
-    equality_literals_collector{filter.get(), num_input_columns}.get_equality_literals();
+  auto const eq_literals_collector = equality_literals_collector{filter.get(), num_input_columns};
+  auto const equality_literals     = eq_literals_collector.get_equality_literals();
 
   // Collect schema indices of columns with equality predicate(s)
   std::vector<cudf::size_type> equality_col_schemas;

From 6918a4070528e1aa2330263e1155cf72808b1a19 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 10 Dec 2024 02:08:45 +0000
Subject: [PATCH 69/82] Minor

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 13 ++++++-------
 1 file changed, 6 insertions(+), 7 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 0b16332fa0a..f9f236a6cec 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -246,9 +246,9 @@ class equality_literals_collector : public ast::detail::expression_transformer {
    *
    * @return Vectors of equality literals, one per input table column
    */
-  [[nodiscard]] cudf::host_span<std::vector<ast::literal*> const> get_equality_literals() const
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals()
   {
-    return {_equality_literals};
+    return std::move(_equality_literals);
   }
 
  private:
@@ -305,8 +305,7 @@ class bloom_filter_expression_converter : public equality_literals_collector {
   /**
    * @brief Delete equality literals getter as no longer needed
    */
-  [[nodiscard]] cudf::host_span<std::vector<ast::literal*> const> get_equality_literals() const =
-    delete;
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() = delete;
 
   // Bring all overloads of `visit` from equality_predicate_collector into scope
   using equality_literals_collector::visit;
@@ -592,8 +591,8 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   auto mr = cudf::get_current_device_resource_ref();
 
   // Collect equality literals for each input table column
-  auto const eq_literals_collector = equality_literals_collector{filter.get(), num_input_columns};
-  auto const equality_literals     = eq_literals_collector.get_equality_literals();
+  auto const equality_literals =
+    equality_literals_collector{filter.get(), num_input_columns}.get_equality_literals();
 
   // Collect schema indices of columns with equality predicate(s)
   std::vector<cudf::size_type> equality_col_schemas;
@@ -668,7 +667,7 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   // Convert AST to BloomfilterAST expression with reference to bloom filter membership
   // in above `bloom_filter_membership_table`
   bloom_filter_expression_converter bloom_filter_expr{
-    filter.get(), num_input_columns, equality_literals};
+    filter.get(), num_input_columns, {equality_literals}};
 
   // Filter bloom filter membership table with the BloomfilterAST expression and collect
   // filtered row group indices

From 85cdc0099f8f29b2644382c13077a25c98fdfb12 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 10 Dec 2024 02:22:02 +0000
Subject: [PATCH 70/82] Make `get_equality_literals()` safe again

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index f9f236a6cec..0b720419fad 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -246,7 +246,7 @@ class equality_literals_collector : public ast::detail::expression_transformer {
    *
    * @return Vectors of equality literals, one per input table column
    */
-  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals()
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() &&
   {
     return std::move(_equality_literals);
   }
@@ -305,7 +305,7 @@ class bloom_filter_expression_converter : public equality_literals_collector {
   /**
    * @brief Delete equality literals getter as no longer needed
    */
-  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() = delete;
+  [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() && = delete;
 
   // Bring all overloads of `visit` from equality_predicate_collector into scope
   using equality_literals_collector::visit;

From fdf8fc87a2a30a75e252aadc032cabab5920e081 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 10 Dec 2024 02:46:15 +0000
Subject: [PATCH 71/82] Update counting_iterator

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 0b720419fad..ba47156a993 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -394,8 +394,8 @@ void read_bloom_filter_data(host_span<std::unique_ptr<datasource> const> sources
 
   // Read bloom filters for all column chunks
   std::for_each(
-    thrust::make_counting_iterator<size_t>(0),
-    thrust::make_counting_iterator<size_t>(num_chunks),
+    thrust::counting_iterator<size_t>(0),
+    thrust::counting_iterator(num_chunks),
     [&](auto const chunk) {
       // If bloom filter offset absent, fill in an empty buffer and skip ahead
       if (not bloom_filter_offsets[chunk].has_value()) {
@@ -504,8 +504,8 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   size_type chunk_count = 0;
 
   // For all data sources
-  std::for_each(thrust::make_counting_iterator<size_t>(0),
-                thrust::make_counting_iterator(row_group_indices.size()),
+  std::for_each(thrust::counting_iterator<size_t>(0),
+                thrust::counting_iterator(row_group_indices.size()),
                 [&](auto const src_index) {
                   // Get all row group indices in the data source
                   auto const& rg_indices = row_group_indices[src_index];
@@ -642,8 +642,8 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   std::vector<std::unique_ptr<cudf::column>> bloom_filter_membership_columns;
   size_t equality_col_idx = 0;
   std::for_each(
-    thrust::make_counting_iterator<size_t>(0),
-    thrust::make_counting_iterator(output_dtypes.size()),
+    thrust::counting_iterator<size_t>(0),
+    thrust::counting_iterator(output_dtypes.size()),
     [&](auto input_col_idx) {
       auto const& dtype = output_dtypes[input_col_idx];
 

From 10a8f5a0b2d45761401551125f89f76bbba6bb58 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 10 Dec 2024 22:07:57 +0000
Subject: [PATCH 72/82] Minor changes

---
 cpp/include/cudf/hashing/detail/xxhash_64.cuh |  3 +--
 cpp/src/io/parquet/arrow_filter_policy.cuh    | 16 +++++++---------
 2 files changed, 8 insertions(+), 11 deletions(-)

diff --git a/cpp/include/cudf/hashing/detail/xxhash_64.cuh b/cpp/include/cudf/hashing/detail/xxhash_64.cuh
index d57cd84efa8..d77d040b365 100644
--- a/cpp/include/cudf/hashing/detail/xxhash_64.cuh
+++ b/cpp/include/cudf/hashing/detail/xxhash_64.cuh
@@ -29,8 +29,7 @@ namespace cudf::hashing::detail {
 
 template <typename Key>
 struct XXHash_64 {
-  using argument_type = Key;
-  using result_type   = std::uint64_t;
+  using result_type = std::uint64_t;
 
   CUDF_HOST_DEVICE constexpr XXHash_64(uint64_t seed = cudf::DEFAULT_HASH_SEED) : _impl{seed} {}
 
diff --git a/cpp/src/io/parquet/arrow_filter_policy.cuh b/cpp/src/io/parquet/arrow_filter_policy.cuh
index dfb6745bed8..74923b46a4a 100644
--- a/cpp/src/io/parquet/arrow_filter_policy.cuh
+++ b/cpp/src/io/parquet/arrow_filter_policy.cuh
@@ -30,8 +30,6 @@ namespace cuco {
  * @brief A policy that defines how Arrow Block-Split Bloom Filter generates and stores a key's
  * fingerprint.
  *
- * @note: This file is a part of cuCollections. Copied here until we get a cuco bump for cudf.
- *
  * Reference:
  * https://github.com/apache/arrow/blob/be1dcdb96b030639c0b56955c4c62f9d6b03f473/cpp/src/parquet/bloom_filter.cc#L219-L230
  *
@@ -41,14 +39,14 @@ namespace cuco {
  * void bulk_insert_and_eval_arrow_policy_bloom_filter(device_vector<KeyType> const& positive_keys,
  *                                                 device_vector<KeyType> const& negative_keys)
  * {
- *     using policy_type = cuco::arrow_filter_policy<key_type>;
+ *     using policy_type = cuco::arrow_filter_policy<KeyType, cuco::xxhash_64>;
  *
  *     // Warn or throw if the number of filter blocks is greater than maximum used by Arrow policy.
  *     static_assert(NUM_FILTER_BLOCKS <= policy_type::max_filter_blocks, "NUM_FILTER_BLOCKS must be
  *                                                                         in range: [1, 4194304]");
  *
  *     // Create a bloom filter with Arrow policy
- *     cuco::bloom_filter<key_type, cuco::extent<size_t>,
+ *     cuco::bloom_filter<KeyType, cuco::extent<size_t>,
  *         cuda::thread_scope_device, policy_type> filter{NUM_FILTER_BLOCKS};
  *
  *     // Add positive keys to the bloom filter
@@ -79,15 +77,15 @@ namespace cuco {
  * @endcode
  *
  * @tparam Key The type of the values to generate a fingerprint for.
+ * @tparam XXHash64 64-bit XXHash hasher implementation for fingerprint generation.
  */
-template <class Key, class Hash>
+template <class Key, template <typename> class XXHash64>
 class arrow_filter_policy {
  public:
-  using hasher             = Hash;           ///< Hash function for Arrow bloom filter policy
+  using hasher             = XXHash64<Key>;  ///< 64-bit XXHash hasher for Arrow bloom filter policy
   using word_type          = std::uint32_t;  ///< uint32_t for Arrow bloom filter policy
-  using hash_argument_type = typename hasher::argument_type;  ///< Hash function input type
-  using hash_result_type   = decltype(std::declval<hasher>()(
-    std::declval<hash_argument_type>()));  ///< hash function output type
+  using hash_argument_type = Key;            ///< Hash function input type
+  using hash_result_type   = std::uint64_t;  ///< hash function output type
 
   static constexpr uint32_t bits_set_per_block = 8;  ///< hardcoded bits set per Arrow filter block
   static constexpr uint32_t words_per_block    = 8;  ///< hardcoded words per Arrow filter block

From d46504fef4253f0b09b7d2d46d584b3c9adf9d91 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 10 Dec 2024 22:12:37 +0000
Subject: [PATCH 73/82] Minor

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 9 ++++-----
 cpp/tests/io/parquet_bloom_filter_test.cu | 5 ++---
 2 files changed, 6 insertions(+), 8 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index ba47156a993..c4c512f7a6f 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -64,8 +64,7 @@ struct bloom_filter_caster {
                                                    rmm::device_async_resource_ref mr) const
   {
     using key_type    = T;
-    using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
-    using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+    using policy_type = cuco::arrow_filter_policy<key_type, cudf::hashing::detail::XXHash_64>;
     using word_type   = typename policy_type::word_type;
 
     // Check if the literal has the same type as the predicate column
@@ -423,9 +422,9 @@ void read_bloom_filter_data(host_span<std::unique_ptr<datasource> const> sources
 
       // Get the hardcoded words_per_block value from `cuco::arrow_filter_policy` using a temporary
       // `std::byte` key type.
-      auto constexpr words_per_block = cuco::arrow_filter_policy<
-        cuda::std::byte,
-        cudf::hashing::detail::XXHash_64<cuda::std::byte>>::words_per_block;
+      auto constexpr words_per_block =
+        cuco::arrow_filter_policy<cuda::std::byte,
+                                  cudf::hashing::detail::XXHash_64>::words_per_block;
 
       // Check if the bloom filter header is valid.
       auto const is_header_valid =
diff --git a/cpp/tests/io/parquet_bloom_filter_test.cu b/cpp/tests/io/parquet_bloom_filter_test.cu
index c290de4568a..827fc4b03b4 100644
--- a/cpp/tests/io/parquet_bloom_filter_test.cu
+++ b/cpp/tests/io/parquet_bloom_filter_test.cu
@@ -36,8 +36,7 @@ class ParquetBloomFilterTest : public cudf::test::BaseFixture {};
 TEST_F(ParquetBloomFilterTest, TestStrings)
 {
   using key_type    = StringType;
-  using hasher_type = cudf::hashing::detail::XXHash_64<key_type>;
-  using policy_type = cuco::arrow_filter_policy<key_type, hasher_type>;
+  using policy_type = cuco::arrow_filter_policy<key_type, cudf::hashing::detail::XXHash_64>;
   using word_type   = policy_type::word_type;
 
   std::size_t constexpr num_filter_blocks = 4;
@@ -65,7 +64,7 @@ TEST_F(ParquetBloomFilterTest, TestStrings)
                      cudf::detail::cuco_allocator<char>>
     filter{num_filter_blocks,
            cuco::thread_scope_device,
-           {hasher_type{cudf::DEFAULT_HASH_SEED}},
+           {{cudf::DEFAULT_HASH_SEED}},
            cudf::detail::cuco_allocator<char>{rmm::mr::polymorphic_allocator<char>{}, stream},
            stream};
 

From c94ce86c84a4289ba18b886c1894cee66acd65a1 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Tue, 10 Dec 2024 22:21:51 +0000
Subject: [PATCH 74/82] Sync arrow filter policy with cuco

---
 cpp/src/io/parquet/arrow_filter_policy.cuh | 17 +++++++----------
 1 file changed, 7 insertions(+), 10 deletions(-)

diff --git a/cpp/src/io/parquet/arrow_filter_policy.cuh b/cpp/src/io/parquet/arrow_filter_policy.cuh
index 74923b46a4a..01f20e86e6c 100644
--- a/cpp/src/io/parquet/arrow_filter_policy.cuh
+++ b/cpp/src/io/parquet/arrow_filter_policy.cuh
@@ -82,10 +82,10 @@ namespace cuco {
 template <class Key, template <typename> class XXHash64>
 class arrow_filter_policy {
  public:
-  using hasher             = XXHash64<Key>;  ///< 64-bit XXHash hasher for Arrow bloom filter policy
-  using word_type          = std::uint32_t;  ///< uint32_t for Arrow bloom filter policy
-  using hash_argument_type = Key;            ///< Hash function input type
-  using hash_result_type   = std::uint64_t;  ///< hash function output type
+  using hasher          = XXHash64<Key>;  ///< 64-bit XXHash hasher for Arrow bloom filter policy
+  using word_type       = std::uint32_t;  ///< uint32_t for Arrow bloom filter policy
+  using key_type        = Key;            ///< Hash function input type
+  using hash_value_type = std::uint64_t;  ///< hash function output type
 
   static constexpr uint32_t bits_set_per_block = 8;  ///< hardcoded bits set per Arrow filter block
   static constexpr uint32_t words_per_block    = 8;  ///< hardcoded words per Arrow filter block
@@ -132,10 +132,7 @@ class arrow_filter_policy {
    *
    * @return The hash value of the key
    */
-  __device__ constexpr hash_result_type hash(hash_argument_type const& key) const
-  {
-    return hash_(key);
-  }
+  __device__ constexpr hash_value_type hash(key_type const& key) const { return hash_(key); }
 
   /**
    * @brief Determines the filter block a key is added into.
@@ -152,7 +149,7 @@ class arrow_filter_policy {
    * @return The block index for the given key's hash value
    */
   template <class Extent>
-  __device__ constexpr auto block_index(hash_result_type hash, Extent num_blocks) const
+  __device__ constexpr auto block_index(hash_value_type hash, Extent num_blocks) const
   {
     constexpr auto hash_bits = cuda::std::numeric_limits<word_type>::digits;
     // TODO: assert if num_blocks > max_filter_blocks
@@ -170,7 +167,7 @@ class arrow_filter_policy {
    *
    * @return The bit pattern for the word/segment in the filter block
    */
-  __device__ constexpr word_type word_pattern(hash_result_type hash, std::uint32_t word_index) const
+  __device__ constexpr word_type word_pattern(hash_value_type hash, std::uint32_t word_index) const
   {
     // SALT array to calculate bit indexes for the current word
     auto constexpr salt = SALT();

From d95a1781019952ec5e5c454a7045e1b77cd037ac Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 12 Dec 2024 10:59:48 +0000
Subject: [PATCH 75/82] Address partial reviewer comments and fix new logger
 header

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index c4c512f7a6f..07a93cde21c 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -24,8 +24,8 @@
 #include <cudf/ast/expressions.hpp>
 #include <cudf/detail/cuco_helpers.hpp>
 #include <cudf/detail/transform.hpp>
-#include <cudf/detail/utilities/logger.hpp>
 #include <cudf/hashing/detail/xxhash_64.cuh>
+#include <cudf/logger.hpp>
 #include <cudf/utilities/span.hpp>
 #include <cudf/utilities/traits.hpp>
 #include <cudf/utilities/type_checks.hpp>
@@ -74,8 +74,7 @@ struct bloom_filter_caster {
       "Mismatched predicate column and literal types");
 
     // Filter properties
-    auto constexpr word_size       = sizeof(word_type);
-    auto constexpr words_per_block = policy_type::words_per_block;
+    auto constexpr bytes_per_block = sizeof(word_type) * policy_type::words_per_block;
 
     rmm::device_buffer results{total_row_groups, stream, mr};
 
@@ -100,7 +99,7 @@ struct bloom_filter_caster {
         }
 
         // Number of filter blocks
-        auto const num_filter_blocks = filter_size / (word_size * words_per_block);
+        auto const num_filter_blocks = filter_size / bytes_per_block;
 
         // Create a bloom filter view.
         cuco::bloom_filter_ref<key_type,

From 840c6e70cbe35ee318564f3d8630de24e1482031 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 12 Dec 2024 22:14:58 +0000
Subject: [PATCH 76/82] Revert to direct dtype check until I find a way to get
 scalar from literal

---
 cpp/src/io/parquet/bloom_filter_reader.cu  | 38 ++++++++++------------
 cpp/src/io/parquet/reader_impl_helpers.hpp |  3 +-
 2 files changed, 20 insertions(+), 21 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 07a93cde21c..f0d8b09640f 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -36,6 +36,7 @@
 
 #include <cuco/bloom_filter_ref.cuh>
 #include <thrust/iterator/counting_iterator.h>
+#include <thrust/tabulate.h>
 
 #include <future>
 #include <numeric>
@@ -68,35 +69,30 @@ struct bloom_filter_caster {
     using word_type   = typename policy_type::word_type;
 
     // Check if the literal has the same type as the predicate column
-    CUDF_EXPECTS(
-      cudf::have_same_types(cudf::column_view{dtype, 0, {}, {}, 0, 0, {}},
-                            cudf::column_view{literal->get_data_type(), 0, {}, {}, 0, 0, {}}),
-      "Mismatched predicate column and literal types");
+    CUDF_EXPECTS(dtype == literal->get_data_type(),
+                 "Mismatched predicate column and literal types");
 
     // Filter properties
     auto constexpr bytes_per_block = sizeof(word_type) * policy_type::words_per_block;
 
     rmm::device_buffer results{total_row_groups, stream, mr};
+    cudf::device_span<bool> results_span{static_cast<bool*>(results.data()), total_row_groups};
 
     // Query literal in bloom filters from each column chunk (row group).
-    thrust::for_each(
+    thrust::tabulate(
       rmm::exec_policy_nosync(stream),
-      thrust::counting_iterator<size_t>{0},
-      thrust::counting_iterator{total_row_groups},
+      results_span.begin(),
+      results_span.end(),
       [filter_span          = bloom_filter_spans.data(),
        d_scalar             = literal->get_value(),
        col_idx              = equality_col_idx,
-       num_equality_columns = num_equality_columns,
-       results = reinterpret_cast<bool*>(results.data())] __device__(auto row_group_idx) {
+       num_equality_columns = num_equality_columns] __device__(auto row_group_idx) {
         // Filter bitset buffer index
         auto const filter_idx  = col_idx + (num_equality_columns * row_group_idx);
         auto const filter_size = filter_span[filter_idx].size();
 
         // If no bloom filter, then fill in `true` as membership cannot be determined
-        if (filter_size == 0) {
-          results[row_group_idx] = true;
-          return;
-        }
+        if (filter_size == 0) { return true; }
 
         // Number of filter blocks
         auto const num_filter_blocks = filter_size / bytes_per_block;
@@ -119,10 +115,10 @@ struct bloom_filter_caster {
                       IS_INT96_TIMESTAMP == is_int96_timestamp::YES) {
           auto const int128_key = static_cast<__int128_t>(d_scalar.value<int64_t>());
           cudf::string_view probe_key{reinterpret_cast<char const*>(&int128_key), 12};
-          results[row_group_idx] = filter.contains(probe_key);
+          return filter.contains(probe_key);
         } else {
           // Query the bloom filter and store results
-          results[row_group_idx] = filter.contains(d_scalar.value<T>());
+          return filter.contains(d_scalar.value<T>());
         }
       });
 
@@ -144,17 +140,19 @@ struct bloom_filter_caster {
     // List, Struct, Dictionary types are not supported
     if constexpr (cudf::is_compound<T>() and not std::is_same_v<T, string_view>) {
       CUDF_FAIL("Compound types don't support equality predicate");
-    } else if constexpr (cudf::is_timestamp<T>()) {
+    }
+
+    // For INT96 timestamps, use cudf::string_view type and set is_int96_timestamp to YES
+    if constexpr (cudf::is_timestamp<T>()) {
       if (parquet_types[equality_col_idx] == Type::INT96) {
         // For INT96 timestamps, use cudf::string_view type and set is_int96_timestamp to YES
         return query_bloom_filter<cudf::string_view, bloom_filter_caster::is_int96_timestamp::YES>(
           equality_col_idx, dtype, literal, stream, mr);
-      } else {
-        return query_bloom_filter<T>(equality_col_idx, dtype, literal, stream, mr);
       }
-    } else {
-      return query_bloom_filter<T>(equality_col_idx, dtype, literal, stream, mr);
     }
+
+    // For all other cases
+    return query_bloom_filter<T>(equality_col_idx, dtype, literal, stream, mr);
   }
 };
 
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index b670c1a63d9..8b9370cb499 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -513,7 +513,8 @@ class named_to_reference_converter : public ast::detail::expression_transformer
  * @param stream CUDA stream used for device memory operations and kernel launches
  * @param mr Device memory resource used to be used in cudf::compute_column
  *
- * @return Collected filtered row group indices, if any.
+ * @return Collected filtered row group indices, one vector per source, if any. A std::nullopt if
+ * all row groups are required or if the computed predicate is all nulls
  */
 [[nodiscard]] std::optional<std::vector<std::vector<size_type>>> collect_filtered_row_group_indices(
   cudf::table_view ast_table,

From 9d8c0714198106941c8eea02eaf616e95d25f0b3 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 12 Dec 2024 22:21:21 +0000
Subject: [PATCH 77/82] Create a dummy scalar of type T and compare with dtype

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 18 ++++++++++--------
 1 file changed, 10 insertions(+), 8 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index f0d8b09640f..326665089c5 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -68,9 +68,16 @@ struct bloom_filter_caster {
     using policy_type = cuco::arrow_filter_policy<key_type, cudf::hashing::detail::XXHash_64>;
     using word_type   = typename policy_type::word_type;
 
-    // Check if the literal has the same type as the predicate column
-    CUDF_EXPECTS(dtype == literal->get_data_type(),
-                 "Mismatched predicate column and literal types");
+    // List, Struct, Dictionary types are not supported
+    if constexpr (cudf::is_compound<T>() and not std::is_same_v<T, string_view>) {
+      CUDF_FAIL("Compound types don't support equality predicate");
+    } else {
+      // Check if the literal has the same type as the predicate column
+      auto const scalar = cudf::scalar_type_t<T>(T{}, false, stream, mr);
+      CUDF_EXPECTS(dtype == literal->get_data_type() and
+                     cudf::have_same_types(cudf::column_view{dtype, 0, {}, {}, 0, 0, {}}, scalar),
+                   "Mismatched predicate column and literal types");
+    }
 
     // Filter properties
     auto constexpr bytes_per_block = sizeof(word_type) * policy_type::words_per_block;
@@ -137,11 +144,6 @@ struct bloom_filter_caster {
                                            rmm::cuda_stream_view stream,
                                            rmm::device_async_resource_ref mr) const
   {
-    // List, Struct, Dictionary types are not supported
-    if constexpr (cudf::is_compound<T>() and not std::is_same_v<T, string_view>) {
-      CUDF_FAIL("Compound types don't support equality predicate");
-    }
-
     // For INT96 timestamps, use cudf::string_view type and set is_int96_timestamp to YES
     if constexpr (cudf::is_timestamp<T>()) {
       if (parquet_types[equality_col_idx] == Type::INT96) {

From 3b8aea0b457cc65ff292ff8ecef7e2ed3c5efdf4 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Thu, 12 Dec 2024 22:23:05 +0000
Subject: [PATCH 78/82] Use a temporary scalar

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 326665089c5..9fe1fc3fce9 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -73,9 +73,9 @@ struct bloom_filter_caster {
       CUDF_FAIL("Compound types don't support equality predicate");
     } else {
       // Check if the literal has the same type as the predicate column
-      auto const scalar = cudf::scalar_type_t<T>(T{}, false, stream, mr);
       CUDF_EXPECTS(dtype == literal->get_data_type() and
-                     cudf::have_same_types(cudf::column_view{dtype, 0, {}, {}, 0, 0, {}}, scalar),
+                     cudf::have_same_types(cudf::column_view{dtype, 0, {}, {}, 0, 0, {}},
+                                           cudf::scalar_type_t<T>(T{}, false, stream, mr)),
                    "Mismatched predicate column and literal types");
     }
 

From c385537c847ec03a77f67bc519f9b0592c83423e Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Fri, 13 Dec 2024 00:58:38 +0000
Subject: [PATCH 79/82] Recalculate `total_row_groups` in apply_bloom_filter

---
 cpp/src/io/parquet/bloom_filter_reader.cu  | 12 +++++++++++-
 cpp/src/io/parquet/predicate_pushdown.cpp  |  9 ++-------
 cpp/src/io/parquet/reader_impl_helpers.hpp |  2 --
 3 files changed, 13 insertions(+), 10 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 9fe1fc3fce9..0d919ed8e78 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -580,12 +580,22 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::ap
   host_span<data_type const> output_dtypes,
   host_span<int const> output_column_schemas,
   std::reference_wrapper<ast::expression const> filter,
-  size_t total_row_groups,
   rmm::cuda_stream_view stream) const
 {
   // Number of input table columns
   auto const num_input_columns = static_cast<cudf::size_type>(output_dtypes.size());
 
+  // Total number of row groups after StatsAST filtration
+  auto const total_row_groups = std::accumulate(
+    input_row_group_indices.begin(),
+    input_row_group_indices.end(),
+    size_t{0},
+    [](size_t sum, auto const& per_file_row_groups) { return sum + per_file_row_groups.size(); });
+
+  // Check if we have less than 2B total row groups.
+  CUDF_EXPECTS(total_row_groups <= std::numeric_limits<cudf::size_type>::max(),
+               "Total number of row groups exceed the size_type's limit");
+
   auto mr = cudf::get_current_device_resource_ref();
 
   // Collect equality literals for each input table column
diff --git a/cpp/src/io/parquet/predicate_pushdown.cpp b/cpp/src/io/parquet/predicate_pushdown.cpp
index 7ae671fbf96..a4eb210c9f0 100644
--- a/cpp/src/io/parquet/predicate_pushdown.cpp
+++ b/cpp/src/io/parquet/predicate_pushdown.cpp
@@ -471,13 +471,8 @@ std::optional<std::vector<std::vector<size_type>>> aggregate_reader_metadata::fi
       : input_row_group_indices;
 
   // Apply bloom filtering on the bloom filter input row groups
-  auto const bloom_filtered_row_groups = apply_bloom_filters(sources,
-                                                             bloom_filter_input_row_groups,
-                                                             output_dtypes,
-                                                             output_column_schemas,
-                                                             filter,
-                                                             total_row_groups,
-                                                             stream);
+  auto const bloom_filtered_row_groups = apply_bloom_filters(
+    sources, bloom_filter_input_row_groups, output_dtypes, output_column_schemas, filter, stream);
 
   // Return bloom filtered row group indices iff collected
   return bloom_filtered_row_groups.has_value() ? bloom_filtered_row_groups
diff --git a/cpp/src/io/parquet/reader_impl_helpers.hpp b/cpp/src/io/parquet/reader_impl_helpers.hpp
index 8b9370cb499..57ff8954a23 100644
--- a/cpp/src/io/parquet/reader_impl_helpers.hpp
+++ b/cpp/src/io/parquet/reader_impl_helpers.hpp
@@ -379,7 +379,6 @@ class aggregate_reader_metadata {
    * @param output_dtypes Datatypes of output columns
    * @param output_column_schemas schema indices of output columns
    * @param filter AST expression to filter row groups based on bloom filter membership
-   * @param total_row_groups Total number of row groups across all data sources
    * @param stream CUDA stream used for device memory operations and kernel launches
    *
    * @return Filtered row group indices, if any is filtered
@@ -390,7 +389,6 @@ class aggregate_reader_metadata {
     host_span<data_type const> output_dtypes,
     host_span<int const> output_column_schemas,
     std::reference_wrapper<ast::expression const> filter,
-    size_t total_row_groups,
     rmm::cuda_stream_view stream) const;
 
   /**

From 3693ad1222f22ad3445af03e398333e40076f9f0 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Fri, 13 Dec 2024 22:46:24 +0000
Subject: [PATCH 80/82] Simplify bloom filter expression with ast::tree and
 handle non-equality operators in the expression

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 41 +++++++++++------------
 1 file changed, 20 insertions(+), 21 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 0d919ed8e78..7e10f59853b 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -178,7 +178,6 @@ class equality_literals_collector : public ast::detail::expression_transformer {
    */
   std::reference_wrapper<ast::expression const> visit(ast::literal const& expr) override
   {
-    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(expr);
     return expr;
   }
 
@@ -191,7 +190,6 @@ class equality_literals_collector : public ast::detail::expression_transformer {
                  "BloomfilterAST supports only left table");
     CUDF_EXPECTS(expr.get_column_index() < _num_input_columns,
                  "Column index cannot be more than number of columns in the table");
-    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(expr);
     return expr;
   }
 
@@ -228,15 +226,11 @@ class equality_literals_collector : public ast::detail::expression_transformer {
         _equality_literals[col_idx].emplace_back(const_cast<ast::literal*>(literal_ptr));
       }
     } else {
-      auto new_operands = visit_operands(operands);
-      if (cudf::ast::detail::ast_operator_arity(op) == 2) {
-        _operators.emplace_back(op, new_operands.front(), new_operands.back());
-      } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
-        _operators.emplace_back(op, new_operands.front());
-      }
+      // Just visit the operands and ignore any output
+      std::ignore = visit_operands(operands);
     }
-    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(_operators.back());
-    return std::reference_wrapper<ast::expression const>(_operators.back());
+
+    return expr;
   }
 
   /**
@@ -263,9 +257,6 @@ class equality_literals_collector : public ast::detail::expression_transformer {
     }
     return transformed_operands;
   }
-  std::optional<std::reference_wrapper<ast::expression const>> _bloom_filter_expr;
-  std::list<ast::column_reference> _col_ref;
-  std::list<ast::operation> _operators;
   size_type _num_input_columns;
 };
 
@@ -337,20 +328,25 @@ class bloom_filter_expression_converter : public equality_literals_collector {
         col_literal_offset += std::distance(equality_literals.cbegin(), literal_iter);
 
         // Evaluate boolean is_true(value) expression as NOT(NOT(value))
-        auto const& value = _col_ref.emplace_back(col_literal_offset);
-        auto const& op    = _operators.emplace_back(ast_operator::NOT, value);
-        _operators.emplace_back(ast_operator::NOT, op);
+        auto const& value = _bloom_filter_expr.push(ast::column_reference{col_literal_offset});
+        _bloom_filter_expr.push(ast::operation{
+          ast_operator::NOT, _bloom_filter_expr.push(ast::operation{ast_operator::NOT, value})});
+      }
+      // For all other expressions, push an always true expression
+      else {
+        _bloom_filter_expr.push(
+          ast::operation{ast_operator::NOT,
+                         _bloom_filter_expr.push(ast::operation{ast_operator::NOT, _always_true})});
       }
     } else {
       auto new_operands = visit_operands(operands);
       if (cudf::ast::detail::ast_operator_arity(op) == 2) {
-        _operators.emplace_back(op, new_operands.front(), new_operands.back());
+        _bloom_filter_expr.push(ast::operation{op, new_operands.front(), new_operands.back()});
       } else if (cudf::ast::detail::ast_operator_arity(op) == 1) {
-        _operators.emplace_back(op, new_operands.front());
+        _bloom_filter_expr.push(ast::operation{op, new_operands.front()});
       }
     }
-    _bloom_filter_expr = std::reference_wrapper<ast::expression const>(_operators.back());
-    return std::reference_wrapper<ast::expression const>(_operators.back());
+    return _bloom_filter_expr.back();
   }
 
   /**
@@ -360,12 +356,15 @@ class bloom_filter_expression_converter : public equality_literals_collector {
    */
   [[nodiscard]] std::reference_wrapper<ast::expression const> get_bloom_filter_expr() const
   {
-    return _bloom_filter_expr.value().get();
+    return _bloom_filter_expr.back();
   }
 
  private:
   std::vector<cudf::size_type> _col_literals_offsets;
   cudf::host_span<std::vector<ast::literal*> const> _equality_literals;
+  ast::tree _bloom_filter_expr;
+  cudf::numeric_scalar<bool> _always_true_scalar{true};
+  ast::literal const _always_true{_always_true_scalar};
 };
 
 /**

From c2de9fb0f474f01842bb1bb894ec7f3ba28021c0 Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <14217455+mhaseeb123@users.noreply.github.com>
Date: Fri, 13 Dec 2024 15:17:03 -0800
Subject: [PATCH 81/82] Apply suggestions from code review

Co-authored-by: Vukasin Milovanovic <vmilovanovic@nvidia.com>
---
 cpp/src/io/parquet/bloom_filter_reader.cu | 12 ++++--------
 1 file changed, 4 insertions(+), 8 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index 7e10f59853b..bd4f90c9e73 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -292,7 +292,7 @@ class bloom_filter_expression_converter : public equality_literals_collector {
   }
 
   /**
-   * @brief Delete equality literals getter as no longer needed
+   * @brief Delete equality literals getter as it's not needed in the derived class
    */
   [[nodiscard]] std::vector<std::vector<ast::literal*>> get_equality_literals() && = delete;
 
@@ -468,13 +468,9 @@ void read_bloom_filter_data(host_span<std::unique_ptr<datasource> const> sources
     });
 
   // Read task sync function
-  auto sync_fn = [](decltype(read_tasks) read_tasks) {
-    for (auto& task : read_tasks) {
-      task.wait();
-    }
-  };
-
-  std::async(std::launch::async, sync_fn, std::move(read_tasks)).wait();
+  for (auto& task : read_tasks) {
+    task.wait();
+  }
 }
 
 }  // namespace

From 344851c176798fd74093b0111a8395fc0b6f37af Mon Sep 17 00:00:00 2001
From: Muhammad Haseeb <mhaseeb@nvidia.com>
Date: Sat, 14 Dec 2024 00:11:29 +0000
Subject: [PATCH 82/82] Minor optimization: Set `have_bloom_filters` while
 populating `bloom_filter_offsets`

---
 cpp/src/io/parquet/bloom_filter_reader.cu | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/cpp/src/io/parquet/bloom_filter_reader.cu b/cpp/src/io/parquet/bloom_filter_reader.cu
index bd4f90c9e73..cc399494fc9 100644
--- a/cpp/src/io/parquet/bloom_filter_reader.cu
+++ b/cpp/src/io/parquet/bloom_filter_reader.cu
@@ -496,6 +496,9 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
   // Gather all bloom filter offsets and sizes.
   size_type chunk_count = 0;
 
+  // Flag to check if we have at least one valid bloom filter offset
+  auto have_bloom_filters = false;
+
   // For all data sources
   std::for_each(thrust::counting_iterator<size_t>(0),
                 thrust::counting_iterator(row_group_indices.size()),
@@ -513,6 +516,9 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
                         bloom_filter_offsets[chunk_count] = col_meta.bloom_filter_offset;
                         bloom_filter_sizes[chunk_count]   = col_meta.bloom_filter_length;
 
+                        // Set `have_bloom_filters` if `bloom_filter_offset` is valid
+                        if (col_meta.bloom_filter_offset.has_value()) { have_bloom_filters = true; }
+
                         // Map each column chunk to its source index
                         chunk_source_map[chunk_count] = src_index;
                         chunk_count++;
@@ -521,9 +527,7 @@ std::vector<rmm::device_buffer> aggregate_reader_metadata::read_bloom_filters(
                 });
 
   // Do we have any bloom filters
-  if (std::any_of(bloom_filter_offsets.cbegin(),
-                  bloom_filter_offsets.cend(),
-                  [](auto const offset) { return offset.has_value(); })) {
+  if (have_bloom_filters) {
     // Vector to hold bloom filter data
     std::vector<rmm::device_buffer> bloom_filter_data(num_chunks);